Stop Thinking, Just Do!

Archive

2024

April

• April 20, 2024 » Bayesian Causal Inference & Propensity Scores
• April 19, 2024 » Understanding Bayesian Statistics Without Frequentist Language
• April 18, 2024 » Prof. Chris Bishop's NEW Deep Learning Textbook!
• April 17, 2024 » Towards Conversational Diagnostic AI
• April 16, 2024 » Anomaly Detection in Continuous-Time Temporal Provenance Graphs
• April 15, 2024 » Gemini Full Breakdown + AlphaCode 2 Bombshell
• April 14, 2024 » Googles GEMINI Just SHOCKED The ENTIRE INDUSTRY!
• April 13, 2024 » Multimodal Prompting with a 44-minute Movie
• April 12, 2024 » Approximate Maximum Matching
• April 11, 2024 » Prompt Engineering, RAG, and Fine-tuning
• April 10, 2024 » Building Production-Ready RAG Applications
• April 9, 2024 » Entropy & Mutual Information in Machine Learning
• April 8, 2024 » Towards Federated Analytics with Local Differential Privacy
• April 7, 2024 » The Science of LLM Benchmarks - Methods, Metrics, and Meanings
• April 6, 2024 » Formal Methods and Machine Learning
• April 5, 2024 » Formal Methods and Deep Learning
• April 4, 2024 » HyperPCM-Robust Task-Conditioned Modeling of Drug-Target Interactions
• April 3, 2024 » Objective-Driven AI
• April 3, 2024 » Explainability of Graph Neural Networks
• April 2, 2024 » Why should you care about DuckDB?
• April 1, 2024 » Dynamic Graph Information Bottleneck

March

• March 31, 2024 » Diffusion Models on Sampling Rare Events
• March 30, 2024 » Deep Probabilistic Models with Tractable Inference
• March 29, 2024 » Nuggets of Shannon Information Theory
• March 28, 2024 » Large Language Models as Copilots for Theorem Proving
• March 27, 2024 » Application Development using Large Language Models
• March 26, 2024 » A New 3D Digital Human Creator For All!
• March 25, 2024 » 나의 문화유산답사기 30주년
• March 24, 2024 » The Fifth Paradigm of Scientific Discovery
• March 23, 2024 » Bringing analytical SQL directly to your Python shell
• March 22, 2024 » Decoding the Information Bottleneck in Self Supervised Learning
• March 21, 2024 » Information Bottleneck Theory of Deep Learning
• March 20, 2024 » MultiDiffusion; Fusing Diffusion Paths for Controlled Image Generation
• March 19, 2024 » In-Process Analytical Data Management with DuckDB
• March 18, 2024 » Generalization in diffusion models
• March 17, 2024 » Gemini Multimodal RAG Applications with LangChain
• March 16, 2024 » Exciting Trends in Machine Learning
• March 15, 2024 » How to Build a Metadata Driven Data Pipelines with Delta Live Tables
• March 14, 2024 » Learn How to Build Real-Time Warehouses on Lakehouse
• March 13, 2024 » Databricks Lakehouse Overview Training
• March 13, 2024 » Simplify ETL pipelines on the Databricks Lakehouse
• March 12, 2024 » Delta Live Tables A to Z; Best Practices for Modern Data
• March 12, 2024 » Building Reliable ETL Pipelines with Azure Databricks
• March 11, 2024 » Graph-based Virtual Sensing
• March 10, 2024 » Online A/B Testing of Real-Time Event Detection Systems
• March 10, 2024 » Machine Unlearning of Features and Labels
• March 9, 2024 » Machine Unlearning Papers
• March 9, 2024 » Ecommerce Marketing Analytics; Top 8 Metrics EXPLAINED
• March 9, 2024 » Differential Privacy and Machine Unlearning
• March 8, 2024 » Foundation Models on Consumer Devices
• March 7, 2024 » Lakehouse with Delta Lake Deep Dive Training
• March 6, 2024 » Large Language Models for Program Optimization
• March 5, 2024 » Multimodal Reasoning; PaLM-E & Gemini
• March 4, 2024 » Text2SQL; The Dream versus Reality
• March 3, 2024 » Data Lakehouse and Data Mesh—Two Sides of the Same Coin
• March 2, 2024 » Pathways Language Model and Model Scaling
• March 1, 2024 » The Information Bottleneck Approaches in Deep Neural Networks

February

• February 29, 2024 » On Mutual Information Estimation
• February 28, 2024 » A Deeper Understanding of Deep Learning
• February 27, 2024 » The Information Bottleneck Theory of Deep Learning
• February 26, 2024 » Information Theory of Deep Learning
• February 25, 2024 » DeepMind Gemini 1.5 - An AI That Remembers!
• February 24, 2024 » Graph Machine Learning for 2024
• February 23, 2024 » Unlock Data Insights Faster with AI-Generated Sample Data
• February 22, 2024 » Graph Dashboards With LLM Powered Natural Language Queries
• February 21, 2024 » Approximate Nearest Neighbor and Product Quantizer
• February 20, 2024 » Choosing the Right Embedding Model, Chunking Strategy, and More
• February 19, 2024 » Document Curation for Retrieval Augmented Generation
• February 18, 2024 » Data Federation with Unity Catalog
• February 17, 2024 » The Data Intelligence Platform
• February 16, 2024 » Cross-Platform Data Lineage with OpenLineage
• February 15, 2024 » Mitigating LLM Hallucinations
• February 14, 2024 » Towards Foundation Models for Knowledge Graph Reasoning
• February 13, 2024 » Unveiling the Power of Multimodal RAG for Images and Text
• February 12, 2024 » Image Similarity Search with Vector Databases
• February 11, 2024 » Building a Music Recommender with Vector Databases
• February 10, 2024 » Document Semantic Search with Vector Databases
• February 9, 2024 » Sentiment Analysis with Vector Databases
• February 8, 2024 » Overview of RAG Approaches with Vector Databases
• February 7, 2024 » Graph-Based Approximate Nearest Neighbors (ANN) and HNSW
• February 6, 2024 » Enhancing Vector Database Queries with Metadata Filtering
• February 5, 2024 » Guiding Graph Embeddings using Path-Ranking Methods
• February 4, 2024 » Evaluating RAG Performance with Vector Databases
• February 3, 2024 » Chunking Best Practices for RAG Applications
• February 2, 2024 » Product quantization in Faiss and from scratch
• February 2, 2024 » Ambient Computing, Multimodal AI & Edge Computing
• February 1, 2024 » Composite AI, the Future of Computing and Human Capital

January

• January 31, 2024 » From Delta Sharing to Clean Rooms
• January 30, 2024 » What is a vector database?
• January 29, 2024 » Advanced RAG; Chunking, Embeddings, and Vector Databases
• January 28, 2024 » Unity Catalog Overview
• January 27, 2024 » How to Build LLMs on Your Company’s Data While on a Budget
• January 26, 2024 » A Technical Deep Dive into Unity Catalog's Practitioner Playbook
• January 25, 2024 » Which is the most reliable estimate?
• January 24, 2024 » Building an LLMOps Stack for Large Language Models
• January 23, 2024 » Introduction to large language models
• January 22, 2024 » Cost Optimization use cases with a Data Catalog
• January 21, 2024 » 5 Explosive Digital Marketing Strategies
• January 20, 2024 » Introduction to Vector Search
• January 20, 2024 » Atlan AI for Documentation -- LIVE Demo
• January 19, 2024 » LLMOps; Everything You Need to Know to Manage LLMs
• January 18, 2024 » How to Train Your Own Large Language Models
• January 17, 2024 » The future of generative AI
• January 16, 2024 » Reset KOREA!, The 1st Seminar
• January 15, 2024 » Intro to Large Language Models
• January 10, 2024 » Metadata Use Cases Demo in Atlan
• January 9, 2024 » The Anatomy of an Active Metadata Platform
• January 8, 2024 » 3 Keys for Collective Intelligence
• January 7, 2024 » Towards Self-Service Analytics

2023

December

• December 26, 2023 » Self-designing Data Systems for the AI Era
• December 8, 2023 » Active Metadata Management
• December 7, 2023 » Active Metadata with Data Quality
• December 6, 2023 » The Next Generation of Active Metadata Platforms
• December 5, 2023 » Knowledge Graph Reasoning with Graph Neural Networks
• December 4, 2023 » The Modern Metadata Platform
• December 3, 2023 » Metadata Management & Data Catalog
• December 2, 2023 » Temporal Graph Benchmark for Machine Learning on Temporal Graphs
• December 1, 2023 » Safely Using Gen AI With Active Metadata and Data Fabric

November

• November 30, 2023 » A General Graph Neural Network Framework for Link Prediction
• November 29, 2023 » Neural Bellman-Ford Networks
• November 28, 2023 » Towards Interpretable Data Science
• November 27, 2023 » Differential Privacy And The Complexity Of Simple Queries
• November 26, 2023 » Privacy Preserving AI
• November 25, 2023 » The Promise of Differential Privacy
• November 24, 2023 » A Survey on Graph Neural Networks for Time Series
• November 23, 2023 » Towards Foundation Models for Knowledge Graph Reasoning
• November 22, 2023 » Stylish Hierarchical Navigable Small World Indexes
• November 21, 2023 » Retrieval-Augmented Language Model Pre-Training
• November 21, 2023 » Domain Knowledge Augmented AI for Databases
• November 20, 2023 » AND/OR Search Spaces for Anytime Probabilistic Reasoning
• November 19, 2023 » Generative AI And Programming
• November 18, 2023 » Gartner's Top 10 Tech Trends for 2024
• November 17, 2023 » Making Retrieval Augmented Generation Better
• November 17, 2023 » Emerging architectures for LLM applications
• November 16, 2023 » Tree of Thought Prompting
• November 16, 2023 » Building a managed database service with Kubernetes Operators
• November 15, 2023 » A Purpose-Built Vector Data Management System
• November 14, 2023 » Best Practices for Query Performance Testing
• November 14, 2023 » OpenAI Embeddings and Vector Databases Crash Course
• November 13, 2023 » Long-Range Genomic Sequence Modeling
• November 12, 2023 » How to Choose a Vector Database
• November 11, 2023 » Awesome Vector Database
• November 10, 2023 » Vector Databases simply explained! (Embeddings & Indexes)
• November 10, 2023 » OpenAI DevDay, Opening Keynote
• November 9, 2023 » Knowledge Distillation
• November 8, 2023 » Vector Database for Large Language Models in Production
• November 7, 2023 » Embeddings, Vector Databases, and Search
• November 6, 2023 » Fast, Approximate Vector Queries on Very Large Unstructured Datasets
• November 5, 2023 » How I make beautiful GRAPHS and PLOTS using LaTeX
• November 4, 2023 » Transformers for Multimodal Self Supervised Learning
• November 3, 2023 » Lance; A Modern Columnar Data Format
• November 2, 2023 » Feature Store Architectures & Technical Challenges
• November 1, 2023 » Machine Learning for Multi-Scale Molecular Simulation and Design

October

• October 31, 2023 » Reasoning Algorithmically; from Toy Experiments to AGI Modules
• October 30, 2023 » Table Representation Learning
• October 29, 2023 » Language Models and Applications in Data Management
• October 28, 2023 » Categories for AI 1; Why Category Theory?
• October 27, 2023 » Estimating Separable Matching Models
• October 26, 2023 » Action Matching; Learning Stochastic Dynamics from Samples
• October 25, 2023 » Categories, Graphs, Reasoning
• October 24, 2023 » Heterogeneous Continual Learning
• October 23, 2023 » Tractable Control for Autoregressive Language Generation
• October 22, 2023 » Approximating the TV Distance Between Two Product Distributions
• October 21, 2023 » The Rise of Tractable Circuits
• October 20, 2023 » Tractable Bounding of Counterfactual Queries
• October 19, 2023 » A Tutorial on Causal Representation Learning
• October 18, 2023 » Explainable Data Drift for NLP
• October 17, 2023 » Open-Source Spotlight - Deepchecks
• October 16, 2023 » Develop test suites for machine learning models and data
• October 15, 2023 » Kolmogorov-Smirnov Test Explained
• October 14, 2023 » L-Infinity Distance Explained
• October 13, 2023 » Wasserstein Distance Explained
• October 12, 2023 » Jensen-Shannon Distance Explained
• October 11, 2023 » Comparison of Data Drift Detection Methods
• October 10, 2023 » Sketching and Projecting
• October 9, 2023 » Randomized Embeddings and Neural Networks
• October 8, 2023 » Memory-Regret Tradeoff for Online Learning
• October 7, 2023 » Sketching Techniques for Kernel Density Estimation
• October 6, 2023 » Fast Attention Requires Bounded Entries
• October 5, 2023 » From Machine Learning to Autonomous Intelligence
• October 4, 2023 » Less is More with PostgresML
• October 3, 2023 » The Power of Graph Learning
• October 2, 2023 » AI-Powered Database Optimization as a Service
• October 1, 2023 » Open Source Vector Search Engine and Vector Database

September

• September 28, 2023 » How to evaluate and explore data drift in ML systems
• September 27, 2023 » Hugging Face Tutorial
• September 26, 2023 » Python and PyTorch Tutorial
• September 25, 2023 » Data Drift & Model Drift Detection Using Python
• September 24, 2023 » Easiest way to Detect Data Drift Using Evidently
• September 23, 2023 » Data Drift Monitoring in Azure ML
• September 22, 2023 » Drifting Away; Testing ML Models in Production
• September 21, 2023 » Multimodal Deep Learning
• September 20, 2023 » Automating Model Monitoring and Drift Detection
• September 19, 2023 » Monitoring Model Quality in Streaming Machine Learning Applications
• September 18, 2023 » ML Drift; Identifying Issues Before You Have a Problem
• September 17, 2023 » Dynamic Graph Algorithms; What We Know and What We Don’t
• September 16, 2023 » How to Understand Clearly
• September 15, 2023 » Gentle Introduction to Causal Inference
• September 14, 2023 » Awesome Incremental Learning / Lifelong learning
• September 13, 2023 » Temporal Distributional Shifts
• September 13, 2023 » A Brief Introduction to Causal Inference
• September 12, 2023 » Explainable Deep Learning for Structured Data
• September 12, 2023 » Leveraging Privacy-Enhancing Technologies with LLMs
• September 11, 2023 » Probabilistic and Logical Circuits for Tractable Causal Reasoning
• September 10, 2023 » Probabilistic Reasoning and Learning for Trustworthy AI
• September 9, 2023 » Learned Query Optimiser At the Forefront of AI Driven Databases
• September 8, 2023 » Internals of Permissioned Blockchains
• September 7, 2023 » On the Role of Neural Collapse in Few-Shot Transfer Learning
• September 6, 2023 » Introduction to Data Structures and Optimization for Fast Algorithms
• September 5, 2023 » Attention Approximates Sparse Distributed Memory
• September 4, 2023 » Fine-Grained Complexity for Dynamic Graph Problems
• September 3, 2023 » Sketching
• September 2, 2023 » Graph Data Structures
• September 1, 2023 » Graph Linear Algebra

August

• August 31, 2023 » Kubeflow vs MLFlow
• August 30, 2023 » Language Models as Statisticians, and as Adapted Organisms
• August 30, 2023 » Differentially Private Sampling from Distributions
• August 29, 2023 » HNSW for Vector Search Explained and Implemented with Faiss
• August 28, 2023 » Incremental View Maintenance
• August 27, 2023 » Preserving Data Privacy in Federated Learning
• August 26, 2023 » On Localization in Language Models
• August 25, 2023 » Meaning in the age of large language models
• August 24, 2023 » Large Language Models Meet Copyright Law
• August 23, 2023 » Logic and Probabilistic Circuits
• August 22, 2023 » Prompt Engineering
• August 21, 2023 » Statistical Learning Theory and Neural Networks
• August 21, 2023 » LangChain "Advanced Retrieval" Webinar
• August 21, 2023 » Challenges and Opportunities in Differentially Private Federated Learning
• August 20, 2023 » LlamaIndex Overview & Use cases
• August 20, 2023 » In-Context Learning
• August 19, 2023 » 9 tips to help you PROVE MATH THEOREMS
• August 19, 2023 » Are LLMs the Beginning or End of NLP?
• August 19, 2023 » Bayesian Principles for Machine Learning
• August 18, 2023 » How to Speak
• August 18, 2023 » Differentially Private GNNs with Aggregation Perturbation
• August 18, 2023 » Recent Advances in Causality-based Recommendation
• August 17, 2023 » Interpretability via Symbolic Distillation
• August 17, 2023 » Synthesizing Relational Data with Differential Privacy
• August 16, 2023 » PrivSyn - Differentially Private Data Synthesis
• August 16, 2023 » Basics of Neurosymbolic Architectures
• August 16, 2023 » The Theory and Practice of Differential Privacy
• August 15, 2023 » Towards Reliable Use of Large Language Models
• August 15, 2023 » Cartel Screening and Machine Learning
• August 14, 2023 » Local Differential Privacy in Practice
• August 14, 2023 » Survey on Privacy/Security in FL
• August 13, 2023 » NVIDIA Keynote at SIGGRAPH 2023
• August 12, 2023 » Trustworthy AI - A Computational Perspective
• August 11, 2023 » High-Dimensional Bayesian Optimization
• August 10, 2023 » Self-Supervised Learning in Recommendation
• August 9, 2023 » Keeping AI under control through mechanistic interpretability
• August 9, 2023 » Towards Machines that can Learn, Reason, and Plan
• August 8, 2023 » Diffusion and Score-Based Generative Models
• August 7, 2023 » Differentially Private Diffusion Models
• August 6, 2023 » Foundation Models and Fair Use
• August 5, 2023 » Spatial Data Science Methods for Improving Models
• August 4, 2023 » Predictive Whittle Networks for Time Series
• August 3, 2023 » There's no such thing as MIRACLE
• August 2, 2023 » Locally Private Graph Neural Network
• August 1, 2023 » What is a Vector Database?

July

• July 31, 2023 » How to write Tree of Thoughts Prompts
• July 31, 2023 » What's the difference between programming and coding
• July 30, 2023 » Prompt Engineering Overview
• July 29, 2023 » A New Upper Bound for the Heilbronn Triangle Problem
• July 28, 2023 » AI and the Future of Humanity
• July 28, 2023 » Two Paths to Intelligence
• July 27, 2023 » Large Multimodal Models
• July 26, 2023 » ChatGPT for Data Analysts
• July 25, 2023 » Visual Prompting Livestream With Andrew Ng
• July 25, 2023 » Quantifying and Understanding Memorization in Deep Neural Networks
• July 24, 2023 » Cross-Platform Data Lineage with OpenLineage
• July 24, 2023 » Continuous Training and Deployment with ZenML and Seldon
• July 23, 2023 » CVPR Highlights 2023
• July 22, 2023 » Robust and Trustworthy Deep Learning
• July 21, 2023 » PFNs; Use neural networks for 100x faster Bayesian predictions
• July 20, 2023 » Multimodal Deep Learning for Protein Engineering
• July 19, 2023 » Topological Deep Learning; Going Beyond Graph Data
• July 18, 2023 » Is Distance Matrix Enough for Geometric Deep Learning?
• July 17, 2023 » Sign and Basis Invariant Networks for Spectral Graph Representation Learning
• July 16, 2023 » Distributed and Multiagent Reinforcement Learning
• July 15, 2023 » A Distributional Multi-agent Reinforcement Learning Approach
• July 14, 2023 » Deploy and Scale Models with BentoML
• July 13, 2023 » Tool Agnostic MLOps with ZenML
• July 12, 2023 » The Four Pillars of Machine Learning
• July 11, 2023 » When to use Kubernetes natively over Kubeflow for ML
• July 10, 2023 » Deploy ZenML + Kubeflow + MLflow + Minio
• July 9, 2023 » MLOps Pipeline Tutorial with ZenML and Kubeflow
• July 8, 2023 » ML models with ZenML and BentoML
• July 7, 2023 » Recent Advances in Vision Foundation Models
• July 6, 2023 » CVPR 2023 Tutorials
• July 5, 2023 » Model Registry and Deployment with MLflow
• July 4, 2023 » How to Deploy ML Models in Production with BentoML
• July 3, 2023 » Data Science–A Systematic Treatment
• July 2, 2023 » LEARN ENGLISH with STEVE JOBS
• July 1, 2023 » DuckDB Internals

June

• June 30, 2023 » How to Master the Art of Leadership
• June 29, 2023 » Getting Started with ZenML
• June 28, 2023 » Generative Models for Language and Vision
• June 27, 2023 » ChatGPT, LLMs & Generative AI; What Your Business Needs to Know
• June 26, 2023 » Differential Privacy & Variants
• June 21, 2023 » Towards Learned Database Systems
• June 20, 2023 » Deep Lake; a Lakehouse for Deep Learning
• June 19, 2023 » Towards Natural Language Query Answering
• June 2, 2023 » Do We Still Need People To Write Database Systems?
• June 1, 2023 » Generative AI and Databases

May

• May 31, 2023 » Contrastive Learning in PyTorch
• May 30, 2023 » Self-Supervised Learning; Self-Prediction and Contrastive Learning
• May 24, 2023 » Discovering Dynamic Salient Regions for Spatio-Temporal Graph Neural Networks
• May 17, 2023 » Bayesian Neural Network
• May 10, 2023 » Study Less Study Smart
• May 9, 2023 » Kubeflow v1.7 Release Overview

April

• April 27, 2023 » Amazon Redshift Internals
• April 26, 2023 » ChatGPT Course – Use The OpenAI API to Code 5 Projects
• April 24, 2023 » Installing and Using NVIDIA Docker
• April 18, 2023 » Hypertree Decompositions
• April 17, 2023 » What is Platform Engineering?
• April 13, 2023 » Databricks Spark SQL / Photon
• April 12, 2023 » Google BigQuery / Dremel
• April 10, 2023 » Personalized Image Generation
• April 9, 2023 » Kubeflow Pipelines 2.0
• April 8, 2023 » Learning to Transfer Knowledge Through Embedding Spaces
• April 7, 2023 » Traffic Prediction with Transfer Learning
• April 7, 2023 » First-Passage Percolation and Related Models
• April 6, 2023 » Sparse Fourier Transform Algorithm for Real-Time Applications
• April 2, 2023 » The Frontier of Deep Learning for Robotics

March

• March 26, 2023 » Microsoft's Products Will Soon Access Open AI Tools Like ChatGPT
• March 25, 2023 » LLaMA & Alpaca; "ChatGPT" On Your Local Computer
• March 23, 2023 » Multi-Objective Recommender Systems

February

• February 27, 2023 » Hands-on Explainable Recommender Systems with Knowledge Graphs
• February 26, 2023 » Improving Recommender Systems with Human in the Loop
• February 12, 2023 » Open-Source Systems for Federated Learning
• February 11, 2023 » An Introduction to Federated Computation
• February 10, 2023 » Data Governance and Sharing on Lakehouse
• February 9, 2023 » Data Mesh and Lakehouse
• February 8, 2023 » Master Data Management
• February 7, 2023 » Setting up Big Data Fabric
• February 6, 2023 » On Future of the Modern Data Stack
• February 1, 2023 » Data Virtualization in Data Fabric

January

• January 31, 2023 » Recommender Systems using Graph Neural Networks
• January 26, 2023 » Activate Your Modern MetaData Stack
• January 24, 2023 » Databricks Lakehouse makes payments ingestion and analytics simple
• January 18, 2023 » The Essential Guide to Data Lineage
• January 17, 2023 » Data Governance Explained in 5 Minutes
• January 16, 2023 » Automated Data Lineage with Unity Catalog
• January 9, 2023 » Active Metadata - Understanding the magic behind the Data Fabric
• January 8, 2023 » Introduction to Data Mesh
• January 7, 2023 » PostgreSQL vs MySQL
• January 6, 2023 » Activate Your Metadata to Empower Innovation
• January 6, 2023 » Accelerating Hybrid Data Mesh Implementation
• January 5, 2023 » Deep-Dive into Delta Lake
• January 4, 2023 » Delta Lake 2.0 Overview
• January 3, 2023 » Advancing Spark - The Photon Whitepaper
• January 2, 2023 » Column-Level Lineage and Active Metadata
• January 1, 2023 » Five Things to Consider About Data Mesh and Data Governance

2022

December

• December 30, 2022 » Data Mesh Implementation Patterns
• December 29, 2022 » Intro to Databricks Lakehouse Platform Architecture and Security
• December 28, 2022 » Meshing About with Databricks
• December 27, 2022 » Enterprise Data Fabric
• December 26, 2022 » Converging Advances to Accelerate Molecular Simulation
• December 26, 2022 » Learning Delaunay Surface Elements for Mesh Reconstruction
• December 26, 2022 » Data Fabric for Self-Driving Cars
• December 23, 2022 » Knowledge Graphs Seminar
• December 19, 2022 » Data Cataloging with Knowledge Graphs
• December 14, 2022 » The Foundation of a Data Fabric
• December 13, 2022 » Data Mesh, Data Fabric, Data Lakehouse
• December 12, 2022 » Tractable Probabilistic Circuits
• December 6, 2022 » Distributed Analytical Database Systems
• December 5, 2022 » GraphZeppelin - Streaming Graph Connectivity at Scale
• December 1, 2022 » Understanding Graph Data Representations in Triplestores

November

• November 30, 2022 » Graph-Powered Data Exploration
• November 29, 2022 » Google BigQuery
• November 28, 2022 » Conformal Prediction Tutorial
• November 21, 2022 » Traffic Prediction Paper Collection
• November 15, 2022 » End-to-end Optimization of Machine Learning Prediction Queries
• November 14, 2022 » Compute Complex Temporal Join Queries Efficiently
• November 8, 2022 » Making Learned Query Optimization Practical
• November 7, 2022 » Universal Database Optimizer
• November 6, 2022 » Machine Learning for Query Optimization
• November 5, 2022 » ML Explainability
• November 4, 2022 » Towards Generalizable Autonomy
• November 4, 2022 » Building an AI and ML ready Modern Data Platform
• November 4, 2022 » Diffusion Probabilistic Modelling of Protein Backbones in 3D
• November 3, 2022 » ICCV Authors Guidelines
• November 2, 2022 » Diffusion Probabilistic Models
• November 1, 2022 » Stable Diffusion - What, Why, How?

October

• October 31, 2022 » Deep Energy-Based Learning
• October 30, 2022 » Incident Prediction in Spatio-Temporal Road Graph Networks
• October 19, 2022 » Diffusion probabilistic modelling of protein backbones in 3D
• October 18, 2022 » Contrastive Learning in PyTorch
• October 17, 2022 » Neural Rendering
• October 10, 2022 » Anatomy of a Research Paper
• October 6, 2022 » Geometric Deep Learning for Drug Discovery
• October 4, 2022 » Deploy Custom Python Model Server
• October 3, 2022 » Contrastive Learning in PyTorch
• October 2, 2022 » InferenceService using a Custom Torchserve Image

September

• September 28, 2022 » From Machine Learning to Autonomous Intelligence
• September 27, 2022 » Towards a Learned Index Structure for ANN Search
• September 15, 2022 » Graph Processing; from Academic Research to Industrial Application
• September 14, 2022 » Katana Graph; A Graph Intelligence Platform
• September 6, 2022 » Machine Learning for Scientific Discovery
• September 2, 2022 » Graph Neural Networks as Gradient Flows

August

• August 4, 2022 » Ab-Initio Potential Energy Surfaces
• August 1, 2022 » Reinforcement Learning via Sequence Modeling

July

• July 30, 2022 » Recipe for a General, Powerful, Scalable Graph Transformer
• July 29, 2022 » Spatial Hash Grids & Tales from Game Development
• July 28, 2022 » Cardinality Estimation Benchmark
• July 27, 2022 » Spatial Indexing in PostGIS
• July 27, 2022 » Data-driven Learned Metric Index; an Unsupervised Approach
• July 26, 2022 » Synopses - Samples, Histogram, Wavelets and Sketches
• July 25, 2022 » Query Execution in MonetDB
• July 24, 2022 » Low overhead self-optimizing storage for compression
• July 23, 2022 » A Database Tuning Tool that "Reads the Manual"
• July 22, 2022 » Rethinking Graph Transformers with Spectral Attention
• July 21, 2022 » Introduction to TorchServe
• July 21, 2022 » MicroK8s Installation & Simple Commands
• July 20, 2022 » Diffusion Models from Scratch in PyTorch
• July 19, 2022 » Deep Learning Theory Lectures
• July 18, 2022 » Kubeflow Fairing
• July 18, 2022 » Kubeflow Fairing, Pipelines, and Training
• July 17, 2022 » On Recoverability of Graph Neural Network Representation
• July 16, 2022 » Deploy Model to KServe
• July 15, 2022 » TorchScript and PyTorch JIT
• July 14, 2022 » Spectra of Graphs and Hypergraphs
• July 14, 2022 » How to Serve PyTorch Models with TorchServe
• July 13, 2022 » A Novel Data Set for Information Retrieval on the Basis of Subgraph Matching
• July 13, 2022 » Graph Embedding in Vector Spaces Using Matching-Graphs
• July 12, 2022 » Google Cloud BigQuery ML Using SQL
• July 11, 2022 » Open World Lifelong Learning
• July 10, 2022 » On Machines that can Learn Continually
• July 9, 2022 » Introduction to Continual Learning
• July 8, 2022 » Introducing OpenAPI Generator
• July 7, 2022 » Kubeflow Development Environment
• July 6, 2022 » KFServing Deep Dive
• July 5, 2022 » Protein structure prediction with AlphaFold
• July 4, 2022 » Deep Learning for Scientific Computation
• July 3, 2022 » Started with AI in Drug Discovery
• July 2, 2022 » Istio Simplified
• July 1, 2022 » Knative and Microk8s with Multipass

June

• June 30, 2022 » KServe in Kubenetes
• June 29, 2022 » Graph Ordering Attention Networks
• June 28, 2022 » Introduction to KServe
• June 27, 2022 » Position-Aware Graph Neural Network using Reachability Estimations
• June 26, 2022 » Isomorphism Using Adjacency Matrix
• June 25, 2022 » Efficient Probabilistic Truss Indexing on Uncertain Graphs
• June 24, 2022 » Toward Verified Artificial Intelligence
• June 23, 2022 » Modern Data Stack
• June 22, 2022 » PyTorchJobClient
• June 22, 2022 » KServe (Kubeflow KFServing) Live Coding Session
• June 21, 2022 » Workflow for ML Projects — MLOps
• June 20, 2022 » Kubeflow Setup
• June 19, 2022 » Introduction to Data Mesh
• June 18, 2022 » Theory of Graph Neural Networks
• June 17, 2022 » Representational Power of Graph Nerual Networks
• June 16, 2022 » Task structure and generalization in graph neural networks
• June 15, 2022 » Geometry Processing with Neural Fields
• June 14, 2022 » Trends in AI
• June 14, 2022 » RelationalAI Knowledge Graph Management System
• June 13, 2022 » Topological Graph Neural Networks
• June 12, 2022 » Causality and (Graph) Neural Networks
• June 11, 2022 » Using Graph Neural Networks for Multi-Node Representation Learning
• June 10, 2022 » Epistemic Uncertainty Estimation for Efficient Search of Drug Candidates
• June 9, 2022 » Toward Neuro Causality
• June 9, 2022 » Connect to MySQL Database from Visual Studio Code
• June 8, 2022 » Data-Efficient Graph Grammar Learning for Molecular Generation
• June 8, 2022 » Rethinking Graph Transformers with Spectral Attention
• June 8, 2022 » How GNNs and Symmetries can help to solve PDEs
• June 7, 2022 » Neural diffusion PDEs, differential geometry, and graph neural networks
• June 7, 2022 » BigQuery ML; Machine Learning with Standard SQL
• June 6, 2022 » GNN with Learnable Structural and Positional Presentations
• June 5, 2022 » Istio Service Mesh 101
• June 5, 2022 » Graph Neural Networks and Diffusion PDEs
• June 4, 2022 » Recommender Systems using Graph Neural Networks
• June 4, 2022 » Manage Multi-tenant ML Workloads Using Istio
• June 4, 2022 » Graph Neural Networks as Neural Diffusion PDEs
• June 3, 2022 » Exploring ML Model Serving with KServe
• June 3, 2022 » Kubeflow Tutorial | Model Serving
• June 3, 2022 » Using AI to accelerate scientific discovery
• June 2, 2022 » Java to MySQL using Visual Studio Code
• June 1, 2022 » Developing the Kubernetes Python Client

May

• May 31, 2022 » Kubernetes Patterns
• May 30, 2022 » Using Visual Studio Code for Java Maven Project
• May 29, 2022 » Mapping External Services
• May 28, 2022 » MiniKF; Kubeflow on your laptop
• May 28, 2022 » Gateway Routing Pattern
• May 27, 2022 » Kubeflow v1.5 Release Overview
• May 26, 2022 » TensorFlow Distributed Training on Kubeflow
• May 25, 2022 » Sidecar Pattern
• May 24, 2022 » YAML
• May 23, 2022 » Kubeflow on macOS
• May 23, 2022 » Why is Kubernetes called K8s?
• May 22, 2022 » Kubernetes Crash Course for Absolute Beginners
• May 21, 2022 » Marrying Top k with Skyline Queries
• May 20, 2022 » Spatial Skyline Queries on Triangulated Irregular Networks
• May 19, 2022 » Challenges and Solutions of Using Kubernetes for Blockchain Applications
• May 18, 2022 » PyTorch Training (PyTorchJob)
• May 18, 2022 » Kubeflow Architecture
• May 18, 2022 » Istio and Service Mesh
• May 17, 2022 » Kubernetes Tutorial for Beginners
• May 17, 2022 » Serving Machine Learning Models at Scale Using KServe
• May 17, 2022 » Advanced Model Inferencing Leveraging Kubeflow Serving
• May 16, 2022 » PyTorch via SQL Commands
• May 15, 2022 » Scaling Shortest Path Graph Queries on Very Large Networks
• May 14, 2022 » Hierarchical Core Maintenance on Large Dynamic Graphs
• May 13, 2022 » Shortest Paths and Centrality in Uncertain Networks
• May 12, 2022 » Bag of Tricks for Node Classification with Graph Neural Networks
• May 11, 2022 » The Case for Learned Index Structures
• May 10, 2022 » Deep Learning for Graph Similarity Search
• May 9, 2022 » HyperSPNs; Compact and Expressive Probabilistic Circuits
• May 8, 2022 » Learned Index Structures for Dynamic and Multi-Dimensional Data
• May 7, 2022 » Blame the Data, Not the System
• May 6, 2022 » Hyperbolic Embeddings in Machine Learning and Deep Learning
• May 5, 2022 » What are Temporal Databases?
• May 4, 2022 » Git Commit Message Style Guide
• May 3, 2022 » What is PrestoDB?
• May 2, 2022 » Spatial, High Dimensional, Temporal Data Indexing and Querying
• May 1, 2022 » A Learned Spatial Index for Range and kNN Queries

April

• April 30, 2022 » An Introduction to Spatial Data and its Applications
• April 29, 2022 » Robustness/Interpretability in Vision & Language Models
• April 28, 2022 » Visual Data Analysis; How? When? Why?
• April 27, 2022 » SageDB; A Self-Assembling Database System
• April 26, 2022 » Towards Zero-Shot Learning for Databases
• April 25, 2022 » From Workload-Driven to Zero-Shot Learning
• April 24, 2022 » From Notebook to Kubeflow Pipelines to KFServing
• April 23, 2022 » Improving Transfer and Robustness of Supervised Contrastive Learning
• April 22, 2022 » Approximate Query Processing
• April 21, 2022 » What are Probabilistic Data Structures?
• April 20, 2022 » Approximation Algorithms for Large Scale Data Analysis
• April 19, 2022 » Modeling Relational Data with Graph Convolution Network
• April 18, 2022 » Open-source Change Data Capture With Debezium
• April 18, 2022 » Finding Approximately Repeated Patterns in Time Series
• April 17, 2022 » Looper; An End-to-End ML Platform for Product Decisions
• April 16, 2022 » Learned Indexing and Sampling for Improving Query Performance
• April 15, 2022 » Principles of Good Machine Learning Systems Design
• April 14, 2022 » Deep Learning Design Patterns
• April 13, 2022 » Tips for Thinking Like a Machine Learning Architect
• April 12, 2022 » Machine Learning Design Patterns
• April 11, 2022 » Introduction to Kubeflow
• April 10, 2022 » Martingale Theory
• April 9, 2022 » Making Architecture Matter
• April 8, 2022 » Bayesian Inference for Big Data
• April 7, 2022 » Architecture and Cardinality Estimations for Graph Queries
• April 6, 2022 » What causes congestion?
• April 5, 2022 » Optimization problems in graphs with locational uncertainty
• April 4, 2022 » Deep Implicit Layers
• April 3, 2022 » Convex Functions
• April 2, 2022 » Quantum Deep Learning
• April 1, 2022 » Uncertainty and Out-of-Distribution Robustness in Deep Learning

March

• March 31, 2022 » Probabilistic Methods for Increased Robustness in Machine Learning
• March 30, 2022 » Probabilistic Circuits - Representations, Inference, Learning and Theory
• March 29, 2022 » FLAT-Fast, Lightweight and Accurate Method for Cardinality Estimation
• March 28, 2022 » Learned Query Scheduling
• March 23, 2022 » A 10 Minute Introduction to Kubeflow
• March 22, 2022 » Ethics of Artificial Intelligence
• March 21, 2022 » What is AI Ethics?
• March 20, 2022 » What is the Cardinality Estimator?
• March 18, 2022 » Qd-tree - Learning Data Layouts for Big Data Analytics
• March 17, 2022 » Sum-Product Networks
• March 16, 2022 » Towards Zero-Shot Learning for Databases
• March 15, 2022 » Machine Learning Design Patterns
• March 14, 2022 » Learned DBMS Components 2.0
• March 13, 2022 » Deep Multi-task and Meta Learning
• March 12, 2022 » Machine Learning Design Patterns - Rebalancing
• March 11, 2022 » Calcite Tutorial
• March 10, 2022 » NeuroCard - One Cardinality Estimator for All Tables

January

• January 12, 2022 » GNN based Recommender Systems
• January 6, 2022 » On the Nature of Data Science
• January 5, 2022 » Breaking the Limit of Graph Neural Networks using Local Mixing Patterns
• January 4, 2022 » Performance Adaptive Sampling Strategy Towards Fast and Accurate Graph Neural Networks
• January 1, 2022 » Data Fabrics for Enterprise Data Management?

2021

December

• December 31, 2021 » Query Optimization and Acceleration at Dremio
• December 30, 2021 » AI4DB & DB4AI-Papers
• December 29, 2021 » Permissioned Blockchains
• December 28, 2021 » Apache Spark, Data Science + Machine Learning
• December 27, 2021 » Introduction to Temporal Graph Neural Networks
• December 26, 2021 » Traffic Forecasting with Pytorch Geometric Temporal
• December 9, 2021 » Geometric Deep Learning
• December 8, 2021 » What Is NFT? - Non Fungible Token
• December 5, 2021 » Deep Recommender Systems
• December 4, 2021 » Weisfeiler and Lehman Go Cellular; CW Networks
• December 3, 2021 » Matrix Multiplication, and the Asymptotic Spectrum Of Tensors
• December 2, 2021 » Traffic Prediction for Intelligent Transport System

November

• November 23, 2021 » Revisiting Knowledge Graph Completion From a Practical Perspective
• November 22, 2021 » Applying Machine Learning-based Database Tuning in Production
• November 21, 2021 » Cloud-Native Ledger Graph Database
• November 17, 2021 » A Probabilistic Model for Joint Inference from Differential Equations
• November 7, 2021 » Optimization Frameworks for Graph Clustering
• November 2, 2021 » Neuralising a Computer Scientist

October

• October 14, 2021 » Preparing For Your Dissertation Defense
• October 13, 2021 » Oral Dissertation Defense Preparation
• October 12, 2021 » How To Defend Your Thesis? Top 10 Tips For Success
• October 11, 2021 » How to Get a PhD in Computer Science
• October 10, 2021 » 100 Thesis Defense Questions in 3 Categories
• October 9, 2021 » 10 Mistakes to Avoid When Defending Your Thesis
• October 8, 2021 » How to prepare for your PhD thesis defence
• October 7, 2021 » Geometric Deep Learning-Past, Present, And Future Optimization
• October 6, 2021 » Optimal Gradient-based Algorithms for Non-concave Bandit Optimization
• October 5, 2021 » How to write a literature review - my simple 5 step process!
• October 4, 2021 » Geometric Deep Learning - from Euclid to drug design
• October 3, 2021 » Graph Isomorphism in Quasipolynomial Time
• October 2, 2021 » Geometric Deep Learning Blueprint
• October 1, 2021 » Geometric Deep Learning-The Erlangen Programme of ML

September

• September 30, 2021 » KDD Cup OGB Large-Scale Challenge
• September 29, 2021 » Theoretical Foundations of Data-Driven Algorithm Design
• September 28, 2021 » Relational Inductive Biases, Deep Learning, and Graph Networks
• September 27, 2021 » The Future Is Big Graphs
• September 26, 2021 » The Universal Approximation Theorem
• September 25, 2021 » Equivariant Networks and Natural Graph Networks
• September 24, 2021 » An Introduction to Hamiltonian Monte Carlo Method for Sampling
• September 23, 2021 » Recurrent Neural Networks for Cognitive Neuroscience
• September 22, 2021 » Permutation Equivariance of Graph Filters
• September 21, 2021 » Graph Convolutional and Isomorphism Networks
• September 20, 2021 » Combinatorial Properties of the Weisfeiler-Leman Algorithm
• September 19, 2021 » Advances in Self-Supervised Learning
• September 18, 2021 » Contrastive Loss, Deep Metric Learning
• September 17, 2021 » Self-Supervised Learning
• September 16, 2021 » Contrastive Learning; A General Self-supervised Learning Approach
• September 15, 2021 » Supervised Contrastive Learning
• September 14, 2021 » What is Noise-Contrastive Estimation?
• September 13, 2021 » GNNs with Learnable Structural and Positional Representation
• September 12, 2021 » Knowledge Graph Representation
• September 11, 2021 » Temporal Graph Networks (TGN)
• September 10, 2021 » Building a Recommender System using Graph Neural Networks
• September 9, 2021 » Junction Tree Variational Autoencoder for Molecular Graph Generation
• September 8, 2021 » Understanding Graph Attention Networks
• September 7, 2021 » GVAE Training and Adjacency Reconstruction
• September 6, 2021 » Graph Representation Learning for Drug Discovery
• September 5, 2021 » Graph Neural Networks for Traffic Prediction
• September 4, 2021 » Visual Exploration of Trajectory Data
• September 3, 2021 » GPS Data Analysis with Python
• September 2, 2021 » 22 Python libraries for Geospatial Data Analysis
• September 1, 2021 » Clustering Trajectories

August

• August 31, 2021 » Towards Causal Representation Learning
• August 30, 2021 » Random Sum Product Networks
• August 29, 2021 » Understanding & Generating Source Code with Graph Neural Networks
• August 28, 2021 » Sum-Product Networks; The Next Generation of Deep Models
• August 27, 2021 » Deep Learning to Discover Coordinates for Dynamics
• August 26, 2021 » The Power of Graph Signal Processing
• August 25, 2021 » Some Mathematical Problems in Graph Signal Processing
• August 24, 2021 » On Laplacian Eigenmaps for Dimensionality Reduction
• August 23, 2021 » Overview of Graph Embeddings
• August 22, 2021 » Sum-Product Networks; Powerful Models with Tractable Inference
• August 21, 2021 » Sum-Product Networks
• August 20, 2021 » Geometric Deep Learning and Reinforcement Learning
• August 19, 2021 » Discovering Genetic Medicines with our AI Drug Discovery Platform
• August 18, 2021 » Proof of Euler's Formula
• August 17, 2021 » GNNs and RL in Traffic Optimization in Cities
• August 16, 2021 » Graph Neural Networks and Applications to Deep Reinforcement Learning
• August 15, 2021 » Writing Scientific Papers
• August 14, 2021 » Drug Discovery with GANs
• August 13, 2021 » PyTorch nn.Embedding()
• August 12, 2021 » Reproducing Kernel Hilbert Spaces
• August 11, 2021 » Dynamical Systems and Machine Learning
• August 10, 2021 » An Introduction to Hilbert Spaces
• August 9, 2021 » Graph Neural Networks in Computational Biology
• August 8, 2021 » What is Euler's Number 'e'?
• August 7, 2021 » Euler's Formula
• August 6, 2021 » The Characteristic Equation and Eigenvalues
• August 5, 2021 » Spanning Trees and Kirchhoff's Theorem
• August 4, 2021 » Acceptance Rate of AI Conferences
• August 3, 2021 » Deep Graph Learning Foundations, Advances and Applications
• August 2, 2021 » Learning Graphs from Data; A Signal Processing Perspective
• August 1, 2021 » Making Graphs Compact by Lossless Contraction

July

• July 31, 2021 » A Short Course in Spectral Graph Theory
• July 30, 2021 » An Introduction to Spectral Graph Theory
• July 29, 2021 » Spectral Graph Theory; Enter Linear Algebra
• July 28, 2021 » Spectral Graph Theory; The Standard Random Walk
• July 27, 2021 » Spectral Graph Theory; The Quadratic Form
• July 26, 2021 » The Laplacian Matrices of Graphs; Algorithms and Applications
• July 25, 2021 » Pragmatic Ridge Spectral Sparsification for Large-Scale Graph Learning
• July 24, 2021 » Knowledge Graph Embeddings Tutorial; From Theory to Practice
• July 23, 2021 » How to use edge features in Graph Neural Networks
• July 22, 2021 » Graph Representation Learning
• July 21, 2021 » Papers on Graph Neural Networks
• July 20, 2021 » A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation
• July 19, 2021 » Super-Constant-Pass Streaming Lower Bounds for Reachability
• July 18, 2021 » Awesone Neural ODE
• July 17, 2021 » Neural Differential Equations
• July 16, 2021 » Generative Adversarial Networks and TF-GAN
• July 15, 2021 » Fairness and Bias in Algorithmic Decision-Making
• July 14, 2021 » A Learned Sketch for Subgraph Counting
• July 13, 2021 » Learning over sets, subgraphs, and streams
• July 12, 2021 » Categorical Reparameterization with Gumbel-Softmax
• July 11, 2021 » A Deterministic Parallel APSP Algorithm and its Applications
• July 10, 2021 » How Do You Generate Synthetic Data?
• July 9, 2021 » Synthetic Tabular Data Generation
• July 8, 2021 » Decremental All-Pairs Shortest Paths in Deterministic Near-Linear Time
• July 7, 2021 » Streaming Lower Bounds for Reachability
• July 6, 2021 » Learning Deep Matrix Factorizations Via Gradient Descent
• July 5, 2021 » NVIDIA Omniverse and a Future of Shared Worlds
• July 4, 2021 » Introduction to Graph Neural Networks
• July 3, 2021 » CVPR 2021 Workshop on Autonomous Vehicles
• July 2, 2021 » Pytorch-BigGraph; A Large Scale Graph Embedding System
• July 1, 2021 » Unsupervised Intelligent Agents

June

• June 30, 2021 » Uncertainty, causality and generalization
• June 29, 2021 » Illustrated Guide to RNN, LSTM, and Transformers
• June 28, 2021 » Banach Space Representer Theorems for Neural Networks
• June 27, 2021 » Next-Generation Recurrent Network Models
• June 26, 2021 » Graph Representation Learning for Drug Discovery
• June 25, 2021 » PostgreSQL Optimizer Methodology
• June 24, 2021 » PPRGo-Scaling Graph Neural Networks with Approximate PageRank
• June 23, 2021 » The Energy-Based Learning Model
• June 22, 2021 » But how does bitcoin actually work?
• June 21, 2021 » Explainable AI Cheat Sheet - Five Key Categories
• June 20, 2021 » Digital Twins and Geospatial Data
• June 19, 2021 » Trends in Traffic Prediction
• June 18, 2021 » Understanding Competencies
• June 17, 2021 » Scaling Up Graph Neural Networks to Large Graphs
• June 16, 2021 » Inductive Logic Programming
• June 15, 2021 » Useful Resources for Traffic Prediction
• June 14, 2021 » A Video Game That Looks Like Reality!
• June 13, 2021 » Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction
• June 12, 2021 » New lower and upper bounds for quantile summary algorithms
• June 11, 2021 » Data Summarization for Machine Learning
• June 10, 2021 » Position aware Graph Neural Networks
• June 9, 2021 » Instacart Data Description
• June 8, 2021 » Fast Counts on Big Data Systems
• June 7, 2021 » MonetDB; Scale Up Before You Scale Out
• June 6, 2021 » Kronecker Graphs, Data Generation, and Performance
• June 5, 2021 » AI+VR; The Kayfabe Life
• June 4, 2021 » Efficient Query Processing Using Machine Learning
• June 3, 2021 » How to use mathcha math online editor
• June 2, 2021 » Uncertainty estimation in supervised learning
• June 1, 2021 » Approximately Bayesian Ensembling

May

• May 31, 2021 » Efficient Data Processing on Modern Hardware
• May 30, 2021 » AI Bias and Fairness
• May 29, 2021 » Generative Models for Graphs
• May 28, 2021 » Evidential Deep Learning and Uncertainty
• May 27, 2021 » Learned Approximate Query Processing
• May 26, 2021 » Meta Learning Tutorial
• May 25, 2021 » Deep Learning Outline
• May 24, 2021 » Transfer Learning
• May 23, 2021 » Approximate nearest neighbor search in high dimensions
• May 22, 2021 » Learning-Based Sketching Algorithms
• May 21, 2021 » Deep Learning Under Distribution Shift
• May 20, 2021 » Principles for Tackling Distribution Shift
• May 19, 2021 » Scalable Graph Neural Networks with Deep Graph Library
• May 18, 2021 » Deep InfoMax
• May 17, 2021 » Introduction to Bandits in Recommender Systems
• May 16, 2021 » Our paper has been published in IEEE Access!
• May 15, 2021 » Constant Girth Approximation for Directed Graphs in Subquadratic Time
• May 14, 2021 » Conditionally optimal approximation algorithms
• May 13, 2021 » Sparsification of Graphs and Matrices
• May 12, 2021 » How to Write a Great Research Paper
• May 11, 2021 » Vision Transformer - Keras Code Examples
• May 10, 2021 » Vision Transformer
• May 9, 2021 » MLP-Mixer; An all-MLP Architecture for Vision
• May 8, 2021 » From AlphaGo to MuZero
• May 7, 2021 » Moral Machines; How culture changes values​?
• May 6, 2021 » Generative Adversarial Networks
• May 5, 2021 » Hardness of Approximation Between P and NP
• May 4, 2021 » GPT-3 = Generation Pre-trained Transformer 3
• May 3, 2021 » Graph Attention Networks Implementation
• May 2, 2021 » Introduction to Pytorch Geometric
• May 1, 2021 » Deep Learning for Graphs

April

• April 30, 2021 » Geometric Deep Learning
• April 29, 2021 » Graph Neural Networks - Models and Applications
• April 22, 2021 » Matching of Matching Graphs
• April 21, 2021 » Graph Classification using Structural Attention
• April 20, 2021 » Approximate Personalized PageRank on Dynamic Graphs
• April 19, 2021 » GCNs for Web-Scale Recommender Systems
• April 18, 2021 » Inductive Representation Learning on Large Graphs
• April 17, 2021 » Write Research Paper Outline
• April 16, 2021 » How to Respond to Reviewer Comments
• April 15, 2021 » Limitations of Graph Neural Networks
• April 14, 2021 » Choice of Graph Representation
• April 13, 2021 » Inductive Representation Learning on Temporal Graphs
• April 12, 2021 » Applications of Graph ML
• April 11, 2021 » Machine Learning with Graphs
• April 10, 2021 » How to Review a Research Paper
• April 9, 2021 » Approximate standing queries on Stream Processing
• April 8, 2021 » Learning Mesh-Based Simulation with Graph Networks
• April 7, 2021 » Temporal Graph Networks for Deep Learning on Dynamic Graphs
• April 6, 2021 » Graph Neural Networks and Knowledge Graph Completion
• April 5, 2021 » Parallel and Distributed Computing in Python with Dask
• April 4, 2021 » Reducing Communication in Graph Neural Network Training
• April 3, 2021 » Mathematical Foundations of the GraphBLAS and Big Data
• April 2, 2021 » Graph Signal Processing - Accounting for Geometry in Data
• April 1, 2021 » Graph Signal Processing for Machine Learning Applications

March

• March 28, 2021 » Papers on Recommendation Systems
• March 27, 2021 » Representational Power of Graph Neural Networks
• March 26, 2021 » Tunable Stream Graph Embeddings at Scale
• March 25, 2021 » Graph Neural Networks
• March 24, 2021 » Graph Convolutional Networks using only NumPy
• March 23, 2021 » Temporal Graph Networks for Dynamic Graphs
• March 22, 2021 » Graph Algorithms as Matrix Vector Products
• March 21, 2021 » Distributed Machine Learning with Python
• March 13, 2021 » Deep Networks Are Kernel Machines
• March 8, 2021 » How the Quest for the Ultimate Learning Machine Will Remake Our World
• March 1, 2021 » Fast Distributed Algorithms for Girth, Cycles and Small Subgraphs

February

• February 28, 2021 » Graph Sketching, Streaming, and Sampling
• February 22, 2021 » Theoretical Foundations of Graph Neural Networks

January

• January 27, 2021 » Efficiently Answering Span Reachability Queries
• January 26, 2021 » Probabilistic Reachability for MDPs
• January 22, 2021 » How computer science can help fight COVID-19
• January 12, 2021 » Enable Digital Transformation with Big Spatial Data & Analytics
• January 11, 2021 » Online Approximation Techniques for Spatial Data
• January 3, 2021 » Sparse Matrices Beyond Solvers

2020

December

• December 19, 2020 » Research Resources for Approximate Query Processing
• December 18, 2020 » Research Directions for Sketching Algorithms
• December 17, 2020 » The Forward-Backward Embedding of Directed Graphs
• December 16, 2020 » The Dynamics of Active Sensing in Social Networks
• December 15, 2020 » Large-scale Graph Representation Learning
• December 14, 2020 » Graph Embedding
• December 13, 2020 » Individual and Collective Graph Mining
• December 11, 2020 » New Machine Learning Tool Tracks Urban Traffic Congestion
• December 7, 2020 » Network Analysis
• December 6, 2020 » Getting Started With Network Datasets
• December 4, 2020 » Bourgain's Embedding
• December 3, 2020 » High Accuracy Protein Structure Prediction Using Deep Learning
• December 2, 2020 » Testing Correlation of Unlabeled Random Graphs
• December 1, 2020 » Designing Effective Scientific Presentations

November

• November 27, 2020 » Quick & Simple Call Graphs in Python
• November 25, 2020 » Latent Network Summarization
• November 20, 2020 » Asymptotic Spectral Distributions for Strongly Regular Graphs
• November 13, 2020 » Graph Convolutional Neural Networks for Molecule Generation
• November 12, 2020 » Deep Learning on Graphs
• November 11, 2020 » Principles and Applications of Relational Inductive Biases
• November 10, 2020 » Traffic Prediction with Advanced Graph Neural Networks
• November 9, 2020 » Papers on Graph Neural Networks
• November 5, 2020 » Self-Driving Databases
• November 1, 2020 » Network Representation Learning

October

• October 31, 2020 » Non-Volatile Memory for Database Management Systems
• October 30, 2020 » Related Papers on Graph Neural Networks
• October 29, 2020 » Finding a New Knowledge
• October 27, 2020 » Beautiful Elastic Simulations, Now Much Faster!
• October 25, 2020 » Approximate Nearest Neighbor Search in High Dimensions
• October 24, 2020 » Billion-scale Approximate Nearest Neighbor Search
• October 19, 2020 » Spatio-Temporal Traffic Prediction Using Deep Learning
• October 18, 2020 » Machine Learning Dissertations
• October 13, 2020 » Research Day
• October 11, 2020 » CS Theory Toolkit
• October 7, 2020 » Deep Learning with PyTorch
• October 6, 2020 » Graph Signal Processing

September

• September 29, 2020 » Deep Learning Lectures
• September 25, 2020 » Convolutional LSTMs for Video Prediction
• September 24, 2020 » Research Proposal
• September 23, 2020 » Nonlinear Dimensionality Reduction
• September 22, 2020 » What Data Platforms Can Do for Machine Learning Workloads
• September 15, 2020 » AI for Neuroscience and Neuroscience for AI
• September 11, 2020 » Optimal Join Algorithms meet Top-k
• September 5, 2020 » Machine Learning Projects Against COVID-19
• September 4, 2020 » Antistrong Digraphs
• September 2, 2020 » Reflections from the Turing Award Winners

August

• August 26, 2020 » Recent Progress in High-Dimensional Learning
• August 25, 2020 » Dynamics of Real Networks - Patterns and Algorithms
• August 24, 2020 » Chasing the COVID-19 Pandemic through Modeling
• August 23, 2020 » This AI Removes Shadows From Your Photos!
• August 21, 2020 » Deep Generative Models for Brain Reading
• August 13, 2020 » Setting Up Your Kubeflow ML Environment
• August 12, 2020 » Statistical Learning Theory for Modern Machine Learning
• August 11, 2020 » Deep Learning for Computer Vision
• August 10, 2020 » Big Ideas in Causality and Machine Learning
• August 8, 2020 » AI for physics & physics for AI
• August 7, 2020 » A Blueprint of Standardized and Composable Machine Learning
• August 6, 2020 » Random Walks on Directed Graphs
• August 5, 2020 » Neural Ordinary Differential Equations
• August 4, 2020 » A Spatio-Temporal U-Network for Graph-structured Time Series Modeling
• August 3, 2020 » Variational Graph Recurrent Neural Networks
• August 2, 2020 » Influence Analytics in Graphs
• August 1, 2020 » Learning from Limited Labeled Data

July

• July 31, 2020 » State of the Industry of Machine Learning Platforms
• July 30, 2020 » Fundamentals of NumPy
• July 29, 2020 » Fundamentals of PyTorch
• July 28, 2020 » Towards Lifelong Learning Machines (L2L)
• July 27, 2020 » Graph Attention Networks
• July 26, 2020 » Learning Equivariant and Hybrid Message Passing on Graphs
• July 25, 2020 » Adversarial Examples and Human-ML Alignment
• July 24, 2020 » Graph Nets; The Next Generation
• July 23, 2020 » Meta-learning
• July 22, 2020 » Meta-learning of Optimizers and Update Rules
• July 21, 2020 » Efficient Deep Learning with Humans in the Loop
• July 20, 2020 » Generalizable Autonomy for Robot Manipulation
• July 19, 2020 » Conditional Channel Gated Networks for Task-Aware Continual Learning
• July 18, 2020 » Transfer/Low-Shot/Semi/Unsupervised Learning
• July 17, 2020 » Mathematical Modeling of Epidemics
• July 16, 2020 » How Behavior Spreads
• July 15, 2020 » Network Diffusion & Contagion
• July 14, 2020 » Explainable AI - Methods, Applications & Recent Developments
• July 13, 2020 » Graph Representation Learning
• July 12, 2020 » The Feature Store
• July 11, 2020 » An Introduction to Meta Learning
• July 10, 2020 » Explainable AI
• July 9, 2020 » Design of BigQuery ML
• July 8, 2020 » Improving Generalization by Self-Training & Self Distillation
• July 7, 2020 » Neurosymbolic AI
• July 6, 2020 » Task dependent adaptive metric for improved few-shot learning

April

• April 24, 2020 » Variational Continual Learning
• April 2, 2020 » Lifelong and Continual Learning

2019

July

• July 28, 2019 » The Power Of BI (Business Intelligence) in Digital Marketing
• July 23, 2019 » Urban Computing
• July 22, 2019 » Urban Computing with Advanced Visualization

June

• June 13, 2019 » IEEE ITEC Best Presentation Award
• June 12, 2019 » Transfer Learning - Part II
• June 11, 2019 » Transfer Learning - Part I
• June 3, 2019 » DeepWalk-Turning Graphs Into Features via Network Embeddings

May

• May 26, 2019 » Graph Embeddings
• May 16, 2019 » Deep Learning on Graphs
• May 15, 2019 » Hybrid Grains
• May 12, 2019 » Graph Signal Processing
• May 7, 2019 » Learning to Learn
• May 4, 2019 » Exploring And Attacking Neural Networks With Activation Atlases
• May 3, 2019 » Miracles of Algebraic Graph Theory
• May 2, 2019 » A History of Spectral Graph Theory and its Applications

April

• April 29, 2019 » The JPEG Compression Algorithm
• April 28, 2019 » Transfer Learning
• April 27, 2019 » Geometric Deep Learning Papers
• April 26, 2019 » Controlling Traffic with Reinforcement Learning
• April 19, 2019 » Ian Goodfellow-Generative Adversarial Networks (GANs)
• April 18, 2019 » Notes on Graph Theory
• April 13, 2019 » Metric Learning and Manifolds
• April 12, 2019 » Awesome Knowledge Distillation
• April 10, 2019 » The Power of Self-Learning Systems
• April 3, 2019 » Variational Inference-Foundations and Modern Methods

March

• March 28, 2019 » 3D Deep Learning
• March 27, 2019 » Machine Learning on Geometrical Data
• March 26, 2019 » Hough Transform for Lines
• March 25, 2019 » Deep Compression
• March 24, 2019 » Model Compression Papers
• March 23, 2019 » Deep RL Bootcamp
• March 21, 2019 » Natural Policy Gradients, TRPO, PPO
• March 20, 2019 » Deep Learning for Recommender Systems
• March 19, 2019 » Awesome Knowledge Distillation
• March 18, 2019 » Knowledge Distillation
• March 17, 2019 » Distill and transfer learning for robust multitask RL
• March 14, 2019 » Geometric Deep Learning
• March 13, 2019 » Visualizing and Understanding Generative Adversarial Networks
• March 8, 2019 » Trust Region Policy Optimization
• March 6, 2019 » Generative Adversarial Imitation Learning
• March 3, 2019 » Google AI's Take on How To Fix Peer Review

February

• February 26, 2019 » Towards Generalization and Efficiency in Reinforcement Learning
• February 22, 2019 » Acceptance Rate of AI Conferences
• February 17, 2019 » PyTorch Geometric
• February 10, 2019 » SQL Query Optimization Meets Deep Reinforcement Learning

January

• January 31, 2019 » Time Series Forecasting using Statistical and Machine Learning Models
• January 29, 2019 » BMM Summer Course 2018 Slides
• January 28, 2019 » A Style-Based Generator Architecture for GAN
• January 25, 2019 » Multi-Agent Reinforcement Learning
• January 24, 2019 » What Makes a Good Image Generator AI?
• January 15, 2019 » Automatic Machine Learning
• January 9, 2019 » Generalizing Convolutions for Deep Learning

2018

December

• December 21, 2018 » Unsupervised Deep Learning

September

• September 29, 2018 » Manifold Learning Yields Insight into Complex Biological State Space

July

• July 6, 2018 » Project Malmo – a platform for fundamental AI research
• July 5, 2018 » Keras vs. PyTorch
• July 4, 2018 » Variational Inference - Foundations and Innovations
• July 2, 2018 » The GAN Zoo
• July 1, 2018 » Beautiful Layered Materials, Instantly

June

• June 26, 2018 » Speed at Scale - Using GPUs to Accelerate Analytics for Extreme Use Cases
• June 25, 2018 » SpatialHadoop - A MapReduce Framework for Big Spatial Data
• June 23, 2018 » From Deep Learning of Disentangled Representations to Higher-level Cognition
• June 22, 2018 » NVIDIA - AI for Generating High-Resolution Images
• June 19, 2018 » Neural Image Stitching And Morphing
• June 13, 2018 » Anomaly Detection for Real-World Systems
• June 12, 2018 » Anomaly Detection
• June 2, 2018 » What Explains Perception in the Brain?

May

• May 29, 2018 » Applied Time Series Econometrics in Python and R
• May 28, 2018 » Time Series Analysis with Python Intermediate
• May 25, 2018 » Two Effective Algorithms for Time Series Forecasting
• May 16, 2018 » AI Learns Painterly Harmonization
• May 15, 2018 » Deep Learning with Ensembles of Neocortical Microcircuits
• May 14, 2018 » A Neural Network Model That Can Reason
• May 12, 2018 » 누구나 할 수 있는 엄청난 몰입력의 5가지 단계
• May 11, 2018 » This AI Reproduces Human Perception
• May 10, 2018 » 미루는 버릇을 완전히 없애주는 '2분짜리 간단한 습관'
• May 9, 2018 » From Generative Models to Generative Agents
• May 7, 2018 » World Models
• May 3, 2018 » What Can Machine Learning Do? Workforce Implications

April

• April 28, 2018 » Introduction to AI for Video Games
• April 27, 2018 » Korea Summit 2018
• April 26, 2018 » 3D Generative-Adversarial Modeling
• April 25, 2018 » Generative Models
• April 24, 2018 » The Design of Traffic Flow Prediction System Based on Multimodal Data
• April 24, 2018 » AI Photo Translation
• April 23, 2018 » Cluster Analysis
• April 22, 2018 » Deepmind AlphaZero - Mastering Games Without Human Knowledge
• April 21, 2018 » NIPS Paper Evaluation Criteria
• April 20, 2018 » Tutorial on GANs
• April 19, 2018 » Equilibrium points in n-person games
• April 18, 2018 » Machine Learning Reports
• April 17, 2018 » Gaussian Material Synthesis
• April 16, 2018 » Sequence Generative Adversarial Nets with Policy Gradient
• April 15, 2018 » The Robot Revolution - The New Age of Manufacturing
• April 14, 2018 » Evolutionary Generative Adversarial Networks
• April 13, 2018 » Time Series Generation with Recurrent Conditional GANs
• April 12, 2018 » Predicting Car Prices using Neural Networks
• April 11, 2018 » Predicting Car Prices - Linear Regression
• April 10, 2018 » Deep Reinforcement Learning
• April 9, 2018 » Brains, Minds and Machines Summer Course
• April 8, 2018 » OpenAI Meta Learning and Self Play
• April 7, 2018 » Time Series Analysis
• April 6, 2018 » Using Support Vector Machines as Flower Finders
• April 5, 2018 » SARSA vs Q-learning
• April 5, 2018 » Building a Neural Network Using the Iris Data Set
• April 4, 2018 » Classification using Decision Trees in R
• April 3, 2018 » The Long-term of AI & Temporal-Difference Learning
• April 2, 2018 » Why we learn?
• April 2, 2018 » Leeds annual traffic growth
• April 1, 2018 » One pixel attack for fooling deep neural networks

March

• March 31, 2018 » Visual Studio Code, CMake and LLDB
• March 30, 2018 » Extreme Team
• March 29, 2018 » Visual Studio Code - C++ Development
• March 28, 2018 » Learning From Scratch
• March 27, 2018 » Cellular Automata
• March 26, 2018 » Radial basis function (RBFs)
• March 25, 2018 » Karush-Kuhn-Tucker Condition
• March 24, 2018 » Boundary Equilibrium Generative Adversarial Networks
• March 23, 2018 » GAN Tutorials
• March 22, 2018 » How To Read a Scientific Research Paper
• March 21, 2018 » UML Tools for Python
• March 20, 2018 » Introduction to gRPC
• March 19, 2018 » Design Patterns in Python
• March 18, 2018 » How to Write a Research Plan
• March 17, 2018 » A Modern Toolkit for Microservice Communication
• March 17, 2018 » All about the GANs
• March 16, 2018 » Predicting Congestion with Tensorflow
• March 15, 2018 » Sequential Implementation of Mesoscopic Simulation
• March 15, 2018 » Processing 100 Billion IoT Events
• March 14, 2018 » Predicting congestion on London's roads with TensorFlow
• March 13, 2018 » Improving Traffic Prediction Using Weather Data
• March 12, 2018 » Limitations of Macroscopic and Mesoscopic Simulation
• March 11, 2018 » Simulation Loop
• March 10, 2018 » Real-Time Data Processing with Apache Flink
• March 9, 2018 » Mesoscopic Simulation
• March 8, 2018 » Mesos Installation
• March 8, 2018 » Building Mesos
• March 7, 2018 » Traffic Prediction
• March 6, 2018 » Just Do It
• March 5, 2018 » An Introduction to Protobufs
• March 4, 2018 » Taking the I out of PaaS with Apache Mesos
• March 3, 2018 » Software Projects Built on Mesos
• March 2, 2018 » Distributed Deep Learning on Mesos
• March 2, 2018 » Apache Mesos and GPUs
• March 1, 2018 » Apache Mesos

February

• February 28, 2018 » Distributed Systems
• February 27, 2018 » High-Performance Mesoscopic Traffic Simulation
• February 26, 2018 » Microscopic Simulation
• February 25, 2018 » Macroscopic Simulation
• February 24, 2018 » Traffic Simulation Background
• February 23, 2018 » Pruning Makes Faster and Smaller Neural Networks
• February 22, 2018 » NIPS 2017 Proceedings
• February 21, 2018 » Distributed TensorFlow
• February 21, 2018 » Using Apache Arrow, Calcite and Parquet to build a Relational Cache
• February 20, 2018 » Data Vocalization
• February 19, 2018 » T tree
• February 18, 2018 » This Autonomous Robot Models Your House Interior
• February 17, 2018 » Reproducibility in Deep Reinforcement Learning
• February 16, 2018 » Google's Text Reader AI
• February 15, 2018 » Conferences 2018
• February 14, 2018 » What Will We Do With Quantum Computing?
• February 13, 2018 » Road Transport Systems
• February 12, 2018 » SLAC Dataset From MIT and Facebook
• February 12, 2018 » OSPRay
• February 11, 2018 » Streaming Through Caches
• February 10, 2018 » GPU Architectures and New Programming Model Features
• February 9, 2018 » Computer Architecture Essentials
• February 8, 2018 » DeepMind Control Suite
• February 7, 2018 » Cellular Automata
• February 6, 2018 » Data Mining Lecture Slides
• February 5, 2018 » What is Quantum Computing?
• February 5, 2018 » AI Research Trends
• February 4, 2018 » Data-Driven Mesoscopic Simulation Models
• February 3, 2018 » Introduction to Geometric Deep Learning
• February 2, 2018 » Geometric Deep Learning Paper and Code
• February 1, 2018 » Geometric Deep Learning

January

• January 31, 2018 » 중세 과학
• January 31, 2018 » Neuromorphic Chip
• January 30, 2018 » 고대 과학
• January 29, 2018 » Pair Programming Tips
• January 28, 2018 » Building Machines That Learn and Think Like People
• January 27, 2018 » TensorTraffic
• January 17, 2018 » Graph Partitioning

2017

December

• December 16, 2017 » Universal Neural Style Transfer
• December 6, 2017 » Testing Software in the Age of Machine Learning

November

• November 15, 2017 » Effective TensorFlow for Non-Experts
• November 4, 2017 » Gartner Top 10 Strategic Technology Trends 2018
• November 3, 2017 » Transferring AI To The Real World (OpenAI)

September

• September 1, 2017 » Natural Language Processing with Deep Learning

July

• July 10, 2017 » Practical Machine Learning Tutorial with Python
• July 9, 2017 » DeepMind's AI Learns Superhuman Relational Reasoning

May

• May 25, 2017 » Self-Illuminating Explosions
• May 16, 2017 » Multi-Agent Reinforcement Learning
• May 15, 2017 » Knowledge Based Artificial Intelligence Part 3 ~ 5
• May 15, 2017 » Introduction to Graph Thinking
• May 14, 2017 » Knowledge Based Artificial Intelligence Part 2
• May 13, 2017 » Knowledge Based Artificial Intelligence Part 1
• May 12, 2017 » Advanced Analytics with Spark
• May 11, 2017 » AI Learns to Synthesize Pictures of Animals
• May 10, 2017 » Latent Dirichlet Allocation Concept
• May 9, 2017 » Mining Massive Data Sets
• May 8, 2017 » An Efficient Scattering Material Representation
• May 7, 2017 » Leveraging Activation Sparsity for Training Deep Neural Networks
• May 6, 2017 » Computability, Complexity, and Theory - Georgia Tech
• May 5, 2017 » Deep Photo Style Transfer
• May 4, 2017 » Reinforcement Learning Course - Georgia Tech
• May 4, 2017 » Digital Transformation in a Connected World
• May 3, 2017 » What is Graph Analytics?
• May 2, 2017 » Gunrock - GPU Graph Analytics
• May 2, 2017 » Graphs in Machine Learning
• May 1, 2017 » AI Creates 3D Models From Faces

April

• April 30, 2017 » Social and Information Network Analysis
• April 29, 2017 » Structural Analysis and Visualization of Networks
• April 28, 2017 » Learning Local Geometric Descriptors from RGB-D Reconstructions
• April 28, 2017 » Machine Learning APIs by Example
• April 27, 2017 » Distributed Optimization via Alternating Direction Method of Multipliers
• April 26, 2017 » Learning and Adaptation
• April 25, 2017 » A modular GPU raytracer using OpenCL for non-interactive graphics
• April 24, 2017 » Semantic Scene Completion from a Single Depth Image
• April 24, 2017 » Latent Space Model for Road Networks to Predict Time-Varying Traffic
• April 23, 2017 » Reinforcement Learning
• April 23, 2017 » Deep Reinforcement Learning
• April 22, 2017 » Analysis and Prediction of Spatiotemporal Traffic Congestion
• April 21, 2017 » Reinforcement Learning Papers
• April 20, 2017 » Technological Singularity
• April 19, 2017 » 학교와 직장의 차이점
• April 18, 2017 » Three Applications of Deep Learning in Big Data Analytics
• April 17, 2017 » Optimization for Machine Learning
• April 16, 2017 » Unsupervised Representation Learning
• April 15, 2017 » Generalization and Equilibrium in Generative Adversarial Networks
• April 14, 2017 » How to train a GAN
• April 13, 2017 » Generative Adversarial Networks (GANs)
• April 12, 2017 » Real-Time Oil Painting on Mobile Hardware
• April 11, 2017 » Deep Advances in Generative Modeling
• April 11, 2017 » A Guide to Edge IoT Analytics
• April 10, 2017 » Edge Accelerated Web Platform
• April 9, 2017 » Edge Computing - IoT and Thinking Machine
• April 9, 2017 » Top AI and Machine Learning Conferences in 2017
• April 8, 2017 » Fog Computing vs. Edge Computing
• April 7, 2017 » Tell Me About Yourself - A Good Answer to This Interview Question
• April 7, 2017 » From Big to Now - The Changing Face of Data
• April 6, 2017 » Fast Data at Internet Scale with Amazon ElastiCache for Redis
• April 5, 2017 » Fast Data, Fast Monitoring
• April 4, 2017 » Geometric Detail Transfer
• April 4, 2017 » Generative Adversarial Networks - Part III
• April 3, 2017 » Generative Adversarial Networks - Part II
• April 2, 2017 » Image Editing with Generative Adversarial Networks
• April 2, 2017 » Generative Adversarial Networks - Part I
• April 2, 2017 » Can we build AI without losing control over it?
• April 1, 2017 » The Review Process for NIPS 2016
• April 1, 2017 » PhD Interview Questions
• April 1, 2017 » Guidelines for Writing a Good NIPS Paper

March

• March 31, 2017 » Graph Streams and Sketches
• March 31, 2017 » CNNs in Practice
• March 30, 2017 » Proceedings of The ICML 2016
• March 30, 2017 » Acceptance Ratio Statistics for Computational Intelligence Conferences
• March 29, 2017 » Machine Learning Papers in AAAI Conference 2017
• March 28, 2017 » Three things you need to know about machine learning
• March 28, 2017 » Artificial Intelligence 3.0 – Third Wave of AI
• March 27, 2017 » Wide & Deep Learning; Memorization + Generalization with TensorFlow
• March 27, 2017 » Keynote - TensorFlow Dev Summit 2017
• March 26, 2017 » Recent Results in Cloud Robotics
• March 25, 2017 » Cloud of Things Overview
• March 24, 2017 » Theory, Practice, and Standardization of Eye-tracking Technology
• March 24, 2017 » Google Developer Day Keynote
• March 23, 2017 » Understanding 3D Shapes With AI
• March 22, 2017 » Occam's Razor
• March 22, 2017 » Blockchain Explained
• March 21, 2017 » Massive Exploration of Neural Machine Translation Architectures
• March 21, 2017 » 5 Technology Trends in 2017 that Change Your Way of Living
• March 20, 2017 » The Evolution of Artificial Intelligence
• March 19, 2017 » Space-Time Video Completion
• March 18, 2017 » How Deep Neural Networks Work
• March 17, 2017 » Stable Neural Style Transfer
• March 16, 2017 » GPU accelerated population annealing algorithm
• March 15, 2017 » Learning Sound Representations from Unlabeled Video
• March 15, 2017 » How to Improve your Clarity of Thought
• March 14, 2017 » Modeling Human Communication Dynamics
• March 13, 2017 » Improving the Neural GPU Architecture for Algorithm Learning
• March 12, 2017 » How to Build an Intelligent Machine
• March 11, 2017 » Introduction to Deep Learning
• March 10, 2017 » Ten Data Acquisition Strategies for Startups
• March 9, 2017 » Automatic Creation of Sketch Tutorials
• March 8, 2017 » Deep Voice; Real-time Neural Text-to-Speech
• March 7, 2017 » Billion-scale similarity search with GPUs
• March 6, 2017 » AI Makes Stunning Photos From Your Drawings
• March 5, 2017 » Data, not algorithms, is key to machine learning success
• March 4, 2017 » The current state of machine intelligence 3.0
• March 3, 2017 » Optimizing Deep CNN-Based Queries over Video Streams at Scale
• March 2, 2017 » Gibbs Sampling-Probabilistic Graphical Models
• March 1, 2017 » Real-time Fiber-level Cloth Rendering

February

• February 28, 2017 » AI; The New Electricity
• February 27, 2017 » Large-Scale Stochastic Learning using GPUs
• February 26, 2017 » Shape and Material from Video
• February 25, 2017 » Artificial Intelligence
• February 24, 2017 » How to Prepare and Deliver a Great TED talk
• February 23, 2017 » Learning to Fill Holes in Images
• February 22, 2017 » Calendar of Computer Graphics Events
• February 21, 2017 » Proceedings of the VLDB Endowment
• February 20, 2017 » Journals and Conferences related to Artificial Intelligence
• February 19, 2017 » AI Builds 3D Models From Images With a Twist
• February 18, 2017 » Major Conferences and Journals about Machine Learning
• February 17, 2017 » Most Cited Deep Learning Papers
• February 16, 2017 » Data Preparation for Machine Learning
• February 15, 2017 » How to Prepare Data For Machine Learning
• February 14, 2017 » IoT, Azure, Machine Learning and more
• February 14, 2017 » How Do Hollywood Movies Render Smoke?
• February 13, 2017 » IBM Watson IoT Platform
• February 12, 2017 » Revisiting Reuse in Main Memory Database Systems
• February 11, 2017 » What's New with NewSQL?
• February 10, 2017 » Spark-GPU; An Accelerated In-Memory Data Processing Engine on Clusters
• February 9, 2017 » Fast Photorealistic Fur and Hair With Cone Tracing
• February 8, 2017 » Big Data and Smart Data
• February 7, 2017 » Deep Natural Language Processing
• February 6, 2017 » What is Artificial Intelligence?
• February 5, 2017 » Universe
• February 4, 2017 » Game AI Development with OpenAI Universe
• February 3, 2017 » Deep Reinforcement Learning - Pong from Pixels
• February 2, 2017 » GPU SQL Query Accelerator
• February 1, 2017 » Multi-core Parallelism in a Column-store

January

• January 31, 2017 » How Intelligent Machines Learn to Make Sense of the World
• January 30, 2017 » Enhance Super Resolution From Google
• January 27, 2017 » Large-Scale Fluid Simulations On Your Graphics Card
• January 26, 2017 » AI Makes 3D Models From Photos
• January 25, 2017 » Attention Transfer
• January 24, 2017 » Text Style Transfer
• January 23, 2017 » IBM Watson-The Power of Artificial Intelligence
• January 23, 2017 » Adaptive Machine Learning for Real-Time Streaming
• January 22, 2017 » AI and Deep Learning at Amazon
• January 21, 2017 » Datasets for Deep Learning
• January 20, 2017 » DataSets and Machine Learning
• January 19, 2017 » Open Data for Deep Learning
• January 18, 2017 » Deep Learning Program Hallucinates Videos
• January 17, 2017 » Reinforcement Learning
• January 16, 2017 » Deep Reinforcement Learning
• January 15, 2017 » Introduction to Deep Learning and Self-Driving Cars
• January 14, 2017 » Deep Learning Resources
• January 13, 2017 » Transfer Learning and Fine-tuning Deep Convolutional Neural Networks
• January 12, 2017 » Amazing Slow Motion Videos With Optical Flow
• January 11, 2017 » Machine Learning Algorithms
• January 10, 2017 » Gunrock
• January 9, 2017 » Neural Network Learns The Physics of Fluids and Smoke
• January 8, 2017 » Recurrent Neural Networks, Image Captioning, LSTM
• January 7, 2017 » The Unreasonable Effectiveness of Recurrent Neural Networks
• January 6, 2017 » Understanding LSTM Networks
• January 5, 2017 » Self-Driving Database Management Systems
• January 4, 2017 » Stunning Video Game Graphics With Voxel Cone Tracing
• January 3, 2017 » Papers that have used pbrt
• January 2, 2017 » Mathematical Methods for Robotics, Vision, and Graphics
• January 1, 2017 » Image Synthesis From Text With Deep Learning

2016

December

• December 30, 2016 » PBRT Installation on macOS
• December 29, 2016 » Water Wave Simulation with Dispersion Kernels
• December 18, 2016 » Crumpling Sound Synthesis
• December 13, 2016 » Introduction to "Physically Based Shading in Theory and Practice"
• December 12, 2016 » Multiphase Fluid Simulations
• December 6, 2016 » Graph Mining for Log Data
• December 5, 2016 » Sound Propagation With Bidirectional Path Tracing
• December 1, 2016 » Understanding Multitenancy and the Architecture of the Salesforce Platform

November

• November 30, 2016 » 3D Printing Acoustic Filters
• November 29, 2016 » Probabilistic Ranking Problem
• November 21, 2016 » Data Blocks; Hybrid OLTP and OLAP on Compressed Storage using both Vectorization and Compilation
• November 20, 2016 » Human Pose Estimation with Deep Learning
• November 19, 2016 » WaveNet by Google DeepMind
• November 11, 2016 » SIGGRAPH 2016 Papers on the Web
• November 8, 2016 » PVLDB Papers
• November 7, 2016 » Progressive skyline computation in database systems
• November 3, 2016 » Proceedings of the VLDB Endowment, Volume 10

October

• October 26, 2016 » IBM Watson Health
• October 21, 2016 » Large Scale Machine Learning
• October 20, 2016 » In-core computation with HyperBall

July

• July 7, 2016 » 소프트웨어 개발의 이해를 돕기 위한 비유

June

• June 29, 2016 » 5 Ways to Make Your Hive Queries Run Faster
• June 20, 2016 » TensorFlow Introduction
• June 15, 2016 » Vectorized Executor
• June 4, 2016 » Skyline Operator
• June 3, 2016 » Fundamentals of Deep Learning
• June 2, 2016 » TensorFlow Tutorial
• June 1, 2016 » TensorFlow Examples

May

• May 31, 2016 » Deep Learning Reading List
• May 30, 2016 » Modeling Colliding and Merging Fluids
• May 29, 2016 » Convolutional Neural Networks for Visual Recognition
• May 28, 2016 » Surface-Only Liquids
• May 27, 2016 » Top 10 Strategic Technology Trends 2016
• May 26, 2016 » IELTS & TOEFL Writing - 5 Common Mistakes
• May 25, 2016 » How to read the genome and build a human being
• May 24, 2016 » The Art of Neural Networks
• May 24, 2016 » Multithreaded Python with OpenMP
• May 23, 2016 » Artistic Style Transfer For Videos
• May 22, 2016 » SIGGRAPH 2016 – Technical Papers Trailer
• May 21, 2016 » Deep Reinforcement Terrain Learning
• May 20, 2016 » Faster In Memory Computing with No Deadlocks
• May 19, 2016 » The Intel® Deep Learning Framework
• May 18, 2016 » Self-Taught Learning and Unsupervised Feature Learning
• May 17, 2016 » Compiling CUDA C/C++ with LLVM
• May 16, 2016 » Separable Subsurface Scattering
• May 15, 2016 » Deep Learning - Intelligence from Big Data
• May 13, 2016 » The Emergence of Converged Data Platforms and the Role of In Memory Computing
• May 12, 2016 » Real-Time Shading With Area Light Sources
• May 12, 2016 » Parallel Data Processing
• May 11, 2016 » Apache Ignite In-Memory Data Fabric
• May 10, 2016 » Smart Data Discovery
• May 9, 2016 » Creating an SPMD Vectorizer for OpenCL with LLVM
• May 8, 2016 » How DeepMind's AlphaGo Defeated Lee Sedol
• May 7, 2016 » The Next Step in GPU-Accelerated Deep Learning
• May 6, 2016 » Convolutional Neural Networks
• May 5, 2016 » Face2Face; Real-Time Facial Reenactment
• May 5, 2016 » Embree; High Performance Ray Tracing Kernels
• May 4, 2016 » Awesome Deep Learning
• May 3, 2016 » Training Deep Neural Networks With Dropout
• May 2, 2016 » Advanced Operating Systems
• May 1, 2016 » Machine Learning Courses

April

• April 30, 2016 » Deep Learning Terms
• April 29, 2016 » Narrow Band Liquid Simulations
• April 28, 2016 » Introduction to HDFS Erasure Coding in Apache Hadoop
• April 26, 2016 » 일상으로의 초대
• April 26, 2016 » Deep Learning for Database Performance Optimization
• April 25, 2016 » No Such Thing As Artificial Intelligence
• April 24, 2016 » Introduction to LLVM
• April 21, 2016 » Min-cost Flow Network Algorithms
• April 20, 2016 » Elasticity with YARN
• April 15, 2016 » Breakthrough Processor and System Design with SPARC M7
• April 14, 2016 » Thread Local Storage
• April 12, 2016 » Life Beyond Column-Stores - Exploiting intra-cycle parallelism
• April 7, 2016 » 아주 짧은 인생을 가치 있게 보내는 법
• April 7, 2016 » gpucc; an open-source GPGPU compiler

March

• March 24, 2016 » Knowledge Curation and Knowledge Fusion
• March 23, 2016 » OLTPBench
• March 22, 2016 » CrowdSky; Skyline Computation with Crowdsourcing
• March 21, 2016 » Photos @ EDBT 2016
• March 21, 2016 » 3D Depth From a Single Photograph
• March 20, 2016 » Automatic Source Transformation from C++ to CUDA using Clang/LLVM
• March 19, 2016 » Efficient Computation of Containment and Complementarity in RDF Data Cubess
• March 19, 2016 » Data Processing in Modern Hardware
• March 18, 2016 » Self-Curating Databases
• March 17, 2016 » Verification of Evolving Graph-structured Data under Expressive Path Constraints
• March 16, 2016 » Top-k Indexes Made Small and Sweet
• March 15, 2016 » Dynamic Graph Queries
• March 14, 2016 » Worst-Case Optimal Algorithms for Parallel Query Processing
• March 13, 2016 » Declarative Probabilistic Programming with Datalog
• March 12, 2016 » Lightning Fast Social Media Analytics
• March 11, 2016 » Research Papers in Computer Graphics
• March 10, 2016 » Statistics-Driven OLAP Acceleration using Query Column Sets
• March 9, 2016 » Readings in Physically Based Rendering
• March 8, 2016 » 9 Cool Deep Learning Applications
• March 7, 2016 » Concurrency Control and Recovery for Search Trees
• March 6, 2016 » Metropolis Light Transport
• March 5, 2016 » How DeepMind Conquered Go With Deep Learning
• March 4, 2016 » 자유가 없는 나라의 공부
• March 3, 2016 » Skip List
• March 2, 2016 » Transactional Memory in Practice
• March 1, 2016 » DB2 for z/OS Best Practice; Locks and Latches
• March 1, 2016 » Database Recovery - Basic Concepts

February

• February 29, 2016 » Latches
• February 28, 2016 » Apache Calcite Overview
• February 27, 2016 » A Better B-Tree in Hekaton
• February 26, 2016 » The Bw-Tree; A B-tree for New Hardware
• February 25, 2016 » Hekaton Research
• February 24, 2016 » Distributed Transactions
• February 23, 2016 » ACID Isolation Level
• February 22, 2016 » Notes About Memory Allocation Redesign
• February 21, 2016 » Postgres Modifications
• February 20, 2016 » The Databaseology Lectures
• February 19, 2016 » C++ Arena Allocation Guide
• February 18, 2016 » Region-based Memory Management
• February 18, 2016 » Redmine Plugin Installation
• February 18, 2016 » PostgreSQL
• February 17, 2016 » 그댄 행복에 살텐데
• February 17, 2016 » Zeppelin Tajo Interpreter
• February 17, 2016 » Data Visualization
• February 16, 2016 » What is VoltDB?
• February 16, 2016 » Release Notes - Tajo - Version 0.11.1
• February 16, 2016 » Peloton Architecture
• February 15, 2016 » Vagrant Tutorial
• February 15, 2016 » Introduction to Vagrant
• February 15, 2016 » Insert-Only Implementation Strategies
• February 14, 2016 » The 5 Leadership Styles
• February 13, 2016 » 등록금 0원
• February 12, 2016 » A Hands-free Adaptive Store
• February 11, 2016 » Emotional Intelligence
• February 10, 2016 » Studying in Germany
• February 10, 2016 » The Bw-Tree Key-Value Store
• February 9, 2016 » Bitmap Indices
• February 8, 2016 » IBM Cognos Analytics
• February 7, 2016 » 민물장어의 꿈
• February 6, 2016 » Understanding the SQL Server Columnstore Index
• February 5, 2016 » Main Memory Databases
• February 4, 2016 » Dictionary-based Order-preserving String Compression
• February 4, 2016 » Hekaton Breaks Through
• February 3, 2016 » The Merits of Data Compression
• February 3, 2016 » DBMS Components
• February 2, 2016 » Compensating Transaction
• February 1, 2016 » In-Memory Column Store Architecture Overview

January

• January 31, 2016 » Advantages & Disadvantages of an In-Memory Database
• January 30, 2016 » Latches, Spinlocks, and Lock Free Data Structures
• January 29, 2016 » Research Topics in Database Management
• January 28, 2016 » Main Memory DBMS
• January 27, 2016 » HYBRID WORKLOADS AND HTAP
• January 26, 2016 » Peloton
• January 25, 2016 » Database Systems Course
• January 24, 2016 » Readings in Parallel Computer Architecture
• January 23, 2016 » Lecture 0 - Course Description and Logistics
• January 22, 2016 » Parallel Computer Architecture Course
• January 21, 2016 » Gartner Top 10 Tech Trends for 2016
• January 20, 2016 » CES 2016 Keynote
• January 19, 2016 » MVCC Overview
• January 18, 2016 » SAP HANA
• January 17, 2016 » Work Breakdown Structure (WBS)
• January 16, 2016 » HYRISE
• January 15, 2016 » Main Compensation and Delta Compensation
• January 14, 2016 » Aggregate Cache
• January 13, 2016 » MonetDB Source compilation on OS X
• January 12, 2016 » SDN and Big Data
• January 11, 2016 » IEEE NetSoft 2016 Call for Demonstrations
• January 10, 2016 » Sparks of Genius
• January 9, 2016 » Connected Components in MapReduce and Beyond
• January 8, 2016 » Analytics in Motion (AIM)
• January 7, 2016 » Big Data is (at least) Four Different Problems
• January 6, 2016 » Papers in Parallel and Distributed Data Management
• January 5, 2016 » If today were the last day
• January 4, 2016 » Real-time Big Data Analytics
• January 3, 2016 » Wearable Technology Trends in 2016
• January 2, 2016 » Telling a Story
• January 1, 2016 » The Scope of a Paper

2015

December

• December 31, 2015 » Queries on Compressed RDDs
• December 30, 2015 » HiBench Suite
• December 29, 2015 » Map-D
• December 28, 2015 » Clang MapReduce
• December 27, 2015 » Rethinking the Role of CPUs in Modern Computers
• December 26, 2015 » MultiQx-GPU
• December 25, 2015 » Concurrent Analytical Query Processing with GPUs
• December 24, 2015 » Where are the GPU based SQL databases?
• December 23, 2015 » Comparing Relational Databases, Memory Cache, and NoSQL
• December 22, 2015 » Oracle In-Memory Database Cache Overview
• December 21, 2015 » MapGraph
• December 20, 2015 » Central Office Re-architected as a Datacenter (CORD)
• December 19, 2015 » Multiprocessor Synchronization
• December 18, 2015 » Software Engineering Principle 3
• December 17, 2015 » Software Engineering Principle 2
• December 16, 2015 » Software Engineering Principle 1
• December 15, 2015 » In-Memory Accelerator for Hadoop
• December 14, 2015 » Main Memory and Streaming Databases
• December 13, 2015 » Building Postgresql on OS X
• December 12, 2015 » Think Fast, Talk Smart
• December 11, 2015 » Unum Computing
• December 10, 2015 » Introducing TPCx-HS Benchmark for Big Data
• December 10, 2015 » Building LuxRender on OS X
• December 9, 2015 » Calendar of Computer Graphics Events
• December 8, 2015 » TPC-H
• December 8, 2015 » LaTeX Fonts on Mac OS X
• December 7, 2015 » Setting Up An Organized Folder Structure
• December 6, 2015 » TPC-DS
• December 5, 2015 » Proceedings of the VLDB Endowment, Volume 9
• December 4, 2015 » In-Memory Data Management Course
• December 3, 2015 » Research Posters 101
• December 2, 2015 » Machine Driven, Human Guided Data Curation for Decision Advantage and Action
• December 1, 2015 » A GPU Parallelized Database Accelerator

November

• November 30, 2015 » Twitter Analysis with Apache Spark and IBM Watson
• November 30, 2015 » Rethinking SQL for Big Data with Apache Drill
• November 30, 2015 » Organizational Charts
• November 29, 2015 » Databaseology Lectures
• November 28, 2015 » KIWI Installation
• November 27, 2015 » IntelliJ IDEA 15
• November 26, 2015 » Maven Support in IntelliJ IDEA
• November 25, 2015 » Zeppelin Deployment
• November 24, 2015 » Zeppelin Structure
• November 24, 2015 » The Pushdown of Everything
• November 23, 2015 » Steve Jobs' Last Words
• November 23, 2015 » 12 Habits of Extraordinarily Motivated People
• November 22, 2015 » Machine Learning as the Key to Personalized Curation
• November 21, 2015 » 22nd ACM SIGKDD Conference
• November 20, 2015 » What is Zeppelin Interpreter
• November 20, 2015 » Writing-up Qualitative Research
• November 19, 2015 » Zeppelin Installation
• November 18, 2015 » MySQL Installation on Ubuntu
• November 17, 2015 » PVLDB 2015 Vol. 9
• November 16, 2015 » Data Engineering Course
• November 15, 2015 » Apache Spark vs. MapReduce
• November 14, 2015 » Korean Constitution
• November 13, 2015 » Database Reading List
• November 12, 2015 » Big Data, Fast Data The Need for In Memory Database Technology
• November 11, 2015 » Arrary DBMS
• November 10, 2015 » Arrary Databases
• November 9, 2015 » Michael Stonebraker's Talk
• November 8, 2015 » Running Hadoop MapReduce on Tachyon
• November 8, 2015 » CUDA LLVM Compiler
• November 7, 2015 » Stanford Compilers Course
• November 6, 2015 » Extreme Scale Computing
• November 5, 2015 » Unit Test using specs
• November 4, 2015 » Scala to Java
• November 3, 2015 » Introduction to LLVM
• November 2, 2015 » MySQL Installation on Mac OS X
• November 1, 2015 » Computer Architecture Recommended Readings

October

• October 31, 2015 » Introduction to Computer Architecture
• October 30, 2015 » What is HTAP?
• October 29, 2015 » Bad Boys Blue Collection
• October 28, 2015 » A Taste of Random Decision Forests on Apache Spark
• October 27, 2015 » ADAM Project
• October 26, 2015 » Privacy as a Practice in Mobile App Development
• October 25, 2015 » Lambda Expression in C++
• October 24, 2015 » Spark - The Ultimate Scala Collections
• October 23, 2015 » BDAS Software Stack
• October 22, 2015 » Basic ONOS Tutorial
• October 21, 2015 » Spark Cluster Configuration
• October 20, 2015 » Legion Bootcamp
• October 19, 2015 » Sample Data
• October 18, 2015 » Building Tachyon Master Branch
• October 17, 2015 » Creating Applications using Spark Streaming
• October 16, 2015 » Creating a Spark Applications
• October 15, 2015 » Working with RDD Operations
• October 14, 2015 » How To Read A Paper
• October 13, 2015 » RAMCloud Presentations
• October 12, 2015 » Teaching creative computer science
• October 11, 2015 » Paper Writing Strategy
• October 10, 2015 » Paper Writing
• October 9, 2015 » BlinkDB Review
• October 8, 2015 » RAMCloud Training
• October 7, 2015 » Kudu - New Apache Hadoop Storage for Fast Analytics on Fast Data
• October 6, 2015 » GridGain In-Memory Data Fabric
• October 5, 2015 » Discardable Memory and Materialized Queries
• October 4, 2015 » 2014 ACM A.M. Turing Lecture
• October 3, 2015 » What is the Future of Hadoop?
• October 2, 2015 » Sparrow Paper Review
• October 1, 2015 » Spark Architecture Shuffle

September

• September 30, 2015 » Explore In-Memory Data Store Tachyon
• September 29, 2015 » Tachyon Overview
• September 28, 2015 » ACM TODS Manuscript Preparation
• September 27, 2015 » Perform SQL Selects on R Data Frames
• September 26, 2015 » R Graphics
• September 25, 2015 » Google's R Style Guide
• September 24, 2015 » Approximate Aggregation Queries in Presto
• September 24, 2015 » Off-heap Memory in Apache Flink and the curious JIT compiler
• September 24, 2015 » AMP Camp 6
• September 23, 2015 » Spark 1.5 DataFrame API Highlights
• September 22, 2015 » Fundamentals of Parallel Computing with the GPU
• September 21, 2015 » Text Mining and Knowledge Graphs in the Cloud
• September 20, 2015 » Knowledge Graph and Cognitive Computing
• September 19, 2015 » Using Presto to combine data from Hive and MySQL
• September 18, 2015 » IBM Watson at Work
• September 18, 2015 » Using HyPer with PostgreSQL Drivers
• September 17, 2015 » Knowledge Graph
• September 16, 2015 » Big Data and Machine Learning - Keys to AI Progress
• September 15, 2015 » 우리는 왜 우리가 되지 못하는가?
• September 14, 2015 » Distributed Computing Conferences
• September 13, 2015 » IEEE Transactions on Knowledge and Data Engineering
• September 12, 2015 » Project Tungsten
• September 11, 2015 » Advantages of Functional Programming
• September 10, 2015 » Building Good Docker Images
• September 9, 2015 » Optimizing Big Data Through Curation
• September 8, 2015 » SparkR Setting for RStudio
• September 7, 2015 » SparkR
• September 6, 2015 » Cognitive Computing
• September 5, 2015 » Spark Lab 3
• September 4, 2015 » Spark Lab 2
• September 3, 2015 » Diving into Spark Streaming's Execution Model
• September 2, 2015 » SAP S4 HANA Technical White Board

August

• August 31, 2015 » Using Electronic Health Records for Better Care
• August 26, 2015 » 6 Big Data Analytics Use Cases for Healthcare IT
• August 24, 2015 » Four Use Cases for Healthcare Predictive Analytics, Big Data
• August 22, 2015 » Five open source Big Data projects to watch
• August 21, 2015 » Reservoir Sampling in MapReduce
• August 20, 2015 » Clinical Data Repository Versus a Data Warehouse
• August 19, 2015 » Top 50 Data Science Resources
• August 18, 2015 » High-throughput, low-latency, and exactly-once stream processing with Apache Flink
• August 17, 2015 » Hyper
• August 16, 2015 » From Big Data to Fast Data
• August 15, 2015 » How Google Works
• August 14, 2015 » SAP Hana In-Memory Explained In Nine Minutes
• August 13, 2015 » Business unIntelligence
• August 12, 2015 » The Challenges of Data Science
• August 12, 2015 » How Data Science Driven Software is Eating the Connected World
• August 11, 2015 » Data Curation as Publishing for the Digital Humanities
• August 10, 2015 » How WellCare Accelerated Big Data Delivery to Improve Analytics
• August 9, 2015 » Sharing Experiences in Cloud Adoption
• August 8, 2015 » IBM Hybrid Transaction Analytic Processing HTAP
• August 7, 2015 » What is Hybrid Transaction/Analytical Processing (HTAP)?
• August 6, 2015 » CIOs and the Ongoing Data Persistence Struggle
• August 6, 2015 » Eight Big Trends in Big Data Analytics
• August 5, 2015 » Hybrid Trasansaction/Analytical Processing (HTAP)
• August 4, 2015 » Hybrid Trasansactional/Analytical Processing (HTAP)
• August 3, 2015 » HTAP and The Future of Data
• August 2, 2015 » Does ethical content curation exist? A data-driven answer
• August 1, 2015 » Stonebraker points to data curation as next integration step

July

• July 31, 2015 » Three Approaches to Scalable Data Curation
• July 30, 2015 » Summarizing
• July 29, 2015 » The Landscape of Big Data, Curation
• July 28, 2015 » Data Curation
• July 27, 2015 » Tackling Data Curation
• July 20, 2015 » OpenMOLE
• July 18, 2015 » Advanced Vector Extension
• July 17, 2015 » How to Write a Good Paper
• July 16, 2015 » Potential Novel Applications of Open SDN
• July 16, 2015 » Hybrid Unified Communications and Collaboration
• July 15, 2015 » What is Visual Thinking?
• July 15, 2015 » Mega-KV, A Case for GPUs to Maximize the Throughput of In-Memory Key-Value Stores
• July 14, 2015 » Ordeal
• July 14, 2015 » Hype Cycle
• July 13, 2015 » Einstein and Buddhism
• July 12, 2015 » SDN Note
• July 11, 2015 » My Top 10 Assertions about Data Warehouses
• July 10, 2015 » RAMCloud Overview
• July 9, 2015 » RAMCloud
• July 9, 2015 » Open Network Operating System
• July 8, 2015 » The Virginian Database
• July 8, 2015 » Function Composition
• July 7, 2015 » Scala Collection
• July 7, 2015 » The Analytical Bootstrap
• July 6, 2015 » CV vs. Resume
• July 5, 2015 » DAQ Introduction
• July 4, 2015 » A New Paradigm for Approximate Query Processing
• July 3, 2015 » You've got to find what you love
• July 2, 2015 » What You're Really Meant to Do
• July 2, 2015 » Understanding the Differences between SDN and Server Virtualization
• July 1, 2015 » Logotherapy

June

• June 30, 2015 » Future of big data analytics
• June 29, 2015 » Five most popular similarity measures implementation in python
• June 28, 2015 » Today
• June 27, 2015 » Mathematical Universe?
• June 27, 2015 » Massive Throughput Database Queries with LLVM on GPUs
• June 26, 2015 » The Power of Inquiry to Spark Breakthrough Ideas
• June 25, 2015 » A More Beautiful Question
• June 24, 2015 » Open Daylight Technical Overview
• June 24, 2015 » Categorical Imperative
• June 23, 2015 » Hadoop + GPU Architecture
• June 23, 2015 » Ballad Music Collection
• June 23, 2015 » Overview of the Apache Flink
• June 22, 2015 » Apache Flink Seminar
• June 21, 2015 » Discussion
• June 20, 2015 » The School of Athens
• June 19, 2015 » Lambda Architecture
• June 19, 2015 » Apache MRQL Installation Instructions
• June 18, 2015 » Common Misconceptions about SQL on Hadoop
• June 18, 2015 » Apache MRQL
• June 17, 2015 » Common Lisp using LLVM and C++ for Molecular Metaprogramming
• June 17, 2015 » Big Data Challenges and Opportunities
• June 16, 2015 » MapD (Massively Parallel Database) Overview
• June 15, 2015 » Data Science using GPUs
• June 15, 2015 » Apache Drill Introduction
• June 14, 2015 » IBM Juices Hadoop With Java On Tesla GPUs
• June 13, 2015 » Apache Tajo Internal
• June 13, 2015 » Broadcast Join in Tajo
• June 12, 2015 » Tajo Cluster Architecture
• June 12, 2015 » Apache Hadoop vs. IBM Platform Symphony and Infosphere BigInsights
• June 12, 2015 » Darwin Day 2015 Questions
• June 11, 2015 » How HPC is Hacking Hadoop
• June 11, 2015 » High-Performance Computing Cluster
• June 10, 2015 » Zeppelin Tutorial
• June 10, 2015 » Teradata Bets Big on Presto for Hadoop SQL
• June 9, 2015 » Introduction to Data Science with Apache Spark
• June 8, 2015 » How to Read a Technical Paper
• June 7, 2015 » The Internet of Things Transforms Transactions with Apache Spark
• June 6, 2015 » Improving Spark for Data Pipelines with Native YARN Integration
• June 6, 2015 » BlinkDB User Guide
• June 5, 2015 » Rethinking SIMD Vectorization for In-Memory Databases
• June 5, 2015 » Introduction to Docker
• June 4, 2015 » Scala idiom - Prefer immutable data structures
• June 3, 2015 » Scala - Tools and Frameworks
• June 3, 2015 » Scala - Pattern Matching
• June 3, 2015 » Scala - Functional/Collection
• June 2, 2015 » Why Scala?
• June 2, 2015 » Introduction to Scala
• June 2, 2015 » Scala - Object Oriented Features
• June 2, 2015 » Scala Installation
• June 2, 2015 » Scala Basics
• June 1, 2015 » Totally Lazy
• June 1, 2015 » A SQL Query Compiler

May

• May 31, 2015 » SIGMOD 2015 Papers
• May 30, 2015 » Recent performance improvements in Apache Spark
• May 29, 2015 » Bringing Spark Closer to Bare Metal
• May 28, 2015 » Best SQL-on-hadoop Tool
• May 27, 2015 » A well-planned kickoff meeting sets the tone for a successful project
• May 26, 2015 » SBT (Simple Build Tool)
• May 26, 2015 » Seven Key Elements for a Successful Kickoff Meeting Agenda
• May 25, 2015 » Data Exploration Using BlinkDB
• May 24, 2015 » Programming With SampleClean
• May 23, 2015 » SampleClean
• May 23, 2015 » Running BlinkDB Locally
• May 22, 2015 » Cornell Notes
• May 21, 2015 » SIGGRAPH 2015 papers on the web
• May 21, 2015 » Large Graph-Mining - Power Tools and a Practitioner's Guide
• May 20, 2015 » Hadoop-RDMA
• May 19, 2015 » SIGGRAPH 2015 - Technical Papers Trailer
• May 18, 2015 » Apache Spark - Caching and Checkpointing Under the Hood
• May 16, 2015 » Tensor Decomposition
• May 15, 2015 » Higher-order Singular Value Decomposition
• May 14, 2015 » Smoothed Analysis of Tensor Decompositions
• May 12, 2015 » Spark for Unconventional Cores
• May 12, 2015 » Aparapi for Unconventional Cores
• May 11, 2015 » Writing An Author Bio
• May 10, 2015 » Apache Phoenix
• May 9, 2015 » Immutability
• May 8, 2015 » Parallelism
• May 7, 2015 » Column Orientation
• May 6, 2015 » Composing and Scaling Data Platforms
• May 6, 2015 » Dependency Injection
• May 5, 2015 » Elements of Scale
• May 4, 2015 » What is Mesos?
• May 3, 2015 » Data Governance Initiative
• May 2, 2015 » Requirements for Cluster Analysis
• May 1, 2015 » What is Cluster Analysis?

April

• April 30, 2015 » Cluster Analysis
• April 29, 2015 » FAQ for the REEF
• April 28, 2015 » Introduction to BlinkDB
• April 27, 2015 » Introduction to REEF
• April 26, 2015 » Readings in Data Management
• April 25, 2015 » Spark with Python Notebook on Mac
• April 25, 2015 » MapReduce for C - Run Native Code in Hadoop
• April 24, 2015 » Spark Notebook
• April 24, 2015 » Spark-GPU Cluster Development in a Notebook
• April 23, 2015 » 5 Ways to Make Your Hive Queries Run Faster
• April 23, 2015 » 39 Data Visualization Tools for Big Data
• April 22, 2015 » How to Write a Paper Efficiently
• April 22, 2015 » HIVE 0.14 Cost Based Optimizer (CBO) Technical Overview
• April 21, 2015 » Setup a JavaCL Maven Project
• April 20, 2015 » Deep Dive into Spark SQL’s Catalyst Optimizer
• April 19, 2015 » GNUPlot Basics
• April 19, 2015 » Introducing DataFrames in Spark for Large Scale Data Science
• April 18, 2015 » Twitter Scalding
• April 17, 2015 » Apache Zeppelin
• April 16, 2015 » Transaction Processing on Confidential Data using Cipherbase
• April 15, 2015 » Introduction to the Spark
• April 14, 2015 » Big Spatial Data Processing using Spark
• April 13, 2015 » SpatialSpark
• April 12, 2015 » New Directions for Spark in 2015
• April 11, 2015 » The Spark SQL Optimizer and External Data Sources API
• April 10, 2015 » How to Prepare for Your Performance Review Meeting
• April 9, 2015 » DataFrame and SQL Operations
• April 8, 2015 » Design Patterns for using foreachRDD
• April 7, 2015 » Output Operations on DStreams
• April 6, 2015 » Transformations on DStreams
• April 5, 2015 » DStream Sources
• April 4, 2015 » Discretized Streams
• April 3, 2015 » Spark Streaming Basic Concepts
• April 2, 2015 » Spark Streaming Quick Example
• April 1, 2015 » Spark Streaming Overview

March

• March 27, 2015 » Passion
• March 26, 2015 » Useful Research Related to Apache Drill
• March 18, 2015 » Google Protocol Buffer Basics - Java
• March 17, 2015 » Apache Spark

February

• February 17, 2015 » An Introduction To Software Defined Networking
• February 16, 2015 » 10 ways to query Hadoop with SQL
• February 13, 2015 » The Bulk Synchronous Parallel Model
• February 12, 2015 » Effective Meeting Strategy
• February 11, 2015 » Application Interaction with the ResourceManager
• February 10, 2015 » Resource Manager
• February 9, 2015 » Build YARN Apps on Hadoop with Apache Slider

January

• January 27, 2015 » Analytic Processing Environment (APE)
• January 26, 2015 » Analytics vs. OLTP
• January 23, 2015 » Layers of Query Processing
• January 22, 2015 » Database Workloads
• January 21, 2015 » Workload Types
• January 20, 2015 » Detailed Characteristics of an Analytic Workload
• January 19, 2015 » Characteristics of an Analytic Workload
• January 13, 2015 » Workload Management for Big Data Analytics
• January 12, 2015 » 11 Core Big Data Workload Design Patterns
• January 5, 2015 » SDN과 NFV와 네트워크 가상화의 차이점 이해하기

2014

December

• December 10, 2014 » Apache Hadoop YARN Architecture
• December 9, 2014 » DryadLINQ

November

• November 20, 2014 » Database Management Systems
• November 19, 2014 » Planning the Approach

October

• October 12, 2014 » Dryad

September

• September 23, 2014 » Join Optimization
• September 19, 2014 » Map-Side Join Vs. Join
• September 18, 2014 » What is map side join and reduce side join?
• September 11, 2014 » Hive Architecture
• September 5, 2014 » Translate from MapReduce to Apache Spark
• September 3, 2014 » Some Common Parallel Patterns
• September 2, 2014 » An Insight into Hadoop YARN NodeManager

August

• August 30, 2014 » Data-based parallelism
• August 29, 2014 » How to fix “System program problem detected” error on Ubuntu
• August 29, 2014 » Task-based parallelism
• August 28, 2014 » Concurrency
• August 27, 2014 » Serial/Parallel Problems
• August 26, 2014 » Multinode Computing
• August 25, 2014 » Hadoop-GIS Spatial Queries
• August 13, 2014 » Running a cluster of virtual machines with Hadoop
• August 13, 2014 » Research skills
• August 12, 2014 » Database Management Systems
• August 11, 2014 » Readings in Database Systems
• August 10, 2014 » SIX sparkling features of Apache Spark!
• August 9, 2014 » Query Optimization Bibliography
• August 9, 2014 » Use Parquet with Impala, Hive, Pig, and MapReduce
• August 8, 2014 » Actian Unleashes SQL Users on Hadoop with Easy Access, Faster Performance
• August 7, 2014 » Presto as a Service
• August 7, 2014 » HIVE as a Service
• August 6, 2014 » Understanding the world of SQL on Hadoop.
• August 5, 2014 » How to Develop Hadoop Tests
• August 4, 2014 » MRUnit Tutorial
• August 3, 2014 » Serialization
• August 3, 2014 » Keep Your Crises Small
• August 3, 2014 » Creativity, Inc. Interview
• August 2, 2014 » HIVE TPC-DS Benchmark
• August 2, 2014 » SIGGRAPH 2014 Technical Papers
• August 2, 2014 » Distributed Computing with Spark
• August 1, 2014 » PostgreSQL

July

• July 31, 2014 » Advantages and Drawbacks of Using Stored Procedures for Processing Data
• July 30, 2014 » Why Oracle Big Data SQL Potentially Solves a Big Issue with Hadoop Security
• July 29, 2014 » Samsung Developer Day 2014 at MWC - Samsung MultiScreen SDK
• July 28, 2014 » Apache Tez Presentation
• July 27, 2014 » Announcing Apache Pig 0.13.0
• July 26, 2014 » Benchmarking Apache Hive 13 for Enterprise Hadoop
• July 25, 2014 » In-Stream Big Data Processing
• July 24, 2014 » Apache Hadoop YARN ResourceManager
• July 23, 2014 » Introduction To Pivotal's Next Generation Analytic Data Lake
• July 23, 2014 » War of the Hadoop SQL engines. And the winner is …?
• July 22, 2014 » Exploring Pivotal HD Single Node (VM)
• July 21, 2014 » How Pivotal Works
• July 20, 2014 » Parquet - Columnar Storage for the People
• July 19, 2014 » Pivotal Big Data Suite
• July 18, 2014 » Pivotal HD Introduction & Demo
• July 17, 2014 » Special "Use Cases" Big Data & Brews - Hortonworks, Pivotal, MapR
• July 16, 2014 » What is Apache Drill?
• July 15, 2014 » Drilling into Big Data with Apache Drill
• July 14, 2014 » Fun with TPC-H (Part 1)
• July 13, 2014 » Implementing Drill Math Functions
• July 12, 2014 » Presto By Facebook – A SQL Engine
• July 11, 2014 » Big Data - The Hadoop Data Warehouse
• July 10, 2014 » Building a Data Warehouse with Hadoop
• July 9, 2014 » Why does MapReduce + GPU Computing?
• July 8, 2014 » Why NoSQL?
• July 7, 2014 » Apache Spark Documentation
• July 6, 2014 » SIGGRAPH 2014 Papers
• July 5, 2014 » Google Cloud Dataflow, a Cloud-native data processing service
• July 4, 2014 » Datawarehouse
• July 3, 2014 » Selecting the right SQL-on-Hadoop engine to access big data
• July 2, 2014 » Big Data Benchmark
• July 1, 2014 » Apache Spark

June

• June 30, 2014 » Optiq
• June 30, 2014 » Adding Acid Transactions in Hive
• June 29, 2014 » Yarn The Key to Overcoming the Challenges of Broad based Hadoop Adoption
• June 28, 2014 » Challenges of Implementing an Advanced SQL Engine on Hadoop
• June 27, 2014 » SparkR Enabling Interactive Data Science at Scale on Hadoop
• June 26, 2014 » Hbase Read High Availability Using Eventually Consistent Region Replicas
• June 25, 2014 » How Hadoop and Hive Change the Data Warehousing Game Forever
• June 24, 2014 » Big Data Management System Smart SQL Processing
• June 23, 2014 » Query Optimization Techniques and JIT based Vectorized Engine
• June 22, 2014 » Pig on Tez - Low Latency ETL with Big Data
• June 21, 2014 » Cost Based Query Optimization in Hive
• June 20, 2014 » Low Latency SQL on Hadoop
• June 19, 2014 » Building a Unified Data Pipeline in Apache Spark
• June 18, 2014 » Big Data Architecture
• June 17, 2014 » Comparing Information Architecture Operational Paradigms
• June 17, 2014 » Big Data Architecture Capabilities
• June 16, 2014 » Grid Architecture and Service Modeling
• June 15, 2014 » How to prepare for SDN
• June 14, 2014 » Features of Cloud and Grid Platforms
• June 13, 2014 » What is SQL-on-Hadoop?
• June 13, 2014 » Apache Storm Basics
• June 12, 2014 » What does “100 times faster than Hive” actually mean?
• June 12, 2014 » GraphX Programming Guide
• June 11, 2014 » TPC Benchmark
• June 11, 2014 » M7 - Native Storage for MapR Tables
• June 11, 2014 » Hadoop 2.4.0 Installation on Mac OS X Mavericks
• June 10, 2014 » Software-Defined Networks
• June 10, 2014 » Future of the Network Documentary
• June 9, 2014 » A Leap Forward With SQL on Hadoop
• June 8, 2014 » Zero-Copy
• June 8, 2014 » Remote Direct Memory Access
• June 7, 2014 » Special "How it Works" Big Data & Brews
• June 7, 2014 » Choosing distribution models
• June 6, 2014 » GPU Programming for the Data Sciences
• June 6, 2014 » 10 undeniable reasons people hate Big Data
• June 5, 2014 » Steve Jobs - One Last Thing
• June 5, 2014 » Physically Based Shading in Theory and Practice
• June 4, 2014 » The Forgotten History Of CGI
• June 3, 2014 » Hadoop Sector will Have Annual Growth of 58% for 2013-2020
• June 2, 2014 » Why Impala Continues to Lead?
• June 1, 2014 » Apache Spark Resource Management and YARN App Models

May

• May 31, 2014 » Camino and Hope
• May 30, 2014 » Camino, Dream and Choice
• May 29, 2014 » Creativity in Business
• May 28, 2014 » Measures of Query Cost
• May 27, 2014 » Query Processing
• May 26, 2014 » Query Transformation
• May 25, 2014 » Database Conferences
• May 24, 2014 » Query Optimizer
• May 23, 2014 » Unit Test
• May 23, 2014 » A Thousand Dreams of You
• May 22, 2014 » Research Topics in Database Systems
• May 21, 2014 » Statistics, Data Mining, Machine Learning and Artificial Intelligence
• May 21, 2014 » ACID Properties of Transactions
• May 20, 2014 » Such a Man
• May 20, 2014 » GTC On-Demand
• May 20, 2014 » Google Spanner
• May 19, 2014 » Open Source Analysis Tips
• May 19, 2014 » Functional Specifications
• May 19, 2014 » Column-Family Stores
• May 18, 2014 » Key-Value and Document Data Models
• May 17, 2014 » Introduction to Distributed Database Management Systems
• May 16, 2014 » Development Tools for Big Data
• May 15, 2014 » Introduction to Data Warehousing
• May 15, 2014 » Apache Tajo JDBC Driver
• May 14, 2014 » Date's Twelve Rules for a DDBMS
• May 14, 2014 » Apache Tajo HCatalog Integration
• May 13, 2014 » Spark for Data Science; A Case Study
• May 13, 2014 » Intel® Xeon Phi™ Coprocessor - the Architecture
• May 13, 2014 » Apache Tajo Backup and Restore
• May 12, 2014 » Apache Tajo Table Partitioning
• May 12, 2014 » An Insight into Hadoop Yarn Resource Manager
• May 11, 2014 » Regression Analysis
• May 11, 2014 » Apache Tajo SequenceFile
• May 11, 2014 » 5 technologies that will help big data cross the chasm
• May 10, 2014 » Apache Tajo Parquet
• May 9, 2014 » How Apache Hadoop YARN HA Works
• May 9, 2014 » Apache Tajo RCFile
• May 8, 2014 » Apache Tajo Table Management
• May 8, 2014 » Apache Tajo CSV (TextFile)
• May 7, 2014 » Papers to Read
• May 7, 2014 » Burndown Chart
• May 7, 2014 » Apache Tajo Functions
• May 6, 2014 » Apache Tajo SQL Language
• May 5, 2014 » Apache Tajo Shell
• May 4, 2014 » Apache Tajo™ 0.8.0 Configuration
• May 3, 2014 » Apache Tajo™ 0.8.0 Released!
• May 3, 2014 » Apache Tajo™ 0.8.0 Documentation
• May 2, 2014 » The Stinger Initiative From HortonWorks With Hadoop
• May 1, 2014 » GPU Cluster
• May 1, 2014 » Bigtable

April

• April 30, 2014 » The Selfish Gene
• April 30, 2014 » GPU Accelerated Computing with C and C++
• April 30, 2014 » Chubby
• April 30, 2014 » Big Data & Brews - Ari Zilka, CTO of Hortonworks' Talk
• April 29, 2014 » The Google File System (GFS)
• April 29, 2014 » Stinger Intiative - Making Apache Hive 100 Times Faster
• April 29, 2014 » Stinger - Interactive Query for Hive
• April 29, 2014 » PageRank Algorithm
• April 29, 2014 » Overview of Data Storage and Coordination Services
• April 28, 2014 » Simple YARN Application
• April 28, 2014 » Underlying Communication Paradigms
• April 28, 2014 » PageRank History
• April 28, 2014 » Overall Architecture and Design Philosophy
• April 27, 2014 » Comparing Apache Tez and Microsoft Dryad
• April 27, 2014 » Apache Spark and Apache Tez
• April 26, 2014 » Introducing the case study - Google
• April 26, 2014 » Integration Tajo with Hive
• April 25, 2014 » Choosing the Right SQL-on-Hadoop
• April 24, 2014 » How to Run a Simple Apache Spark App in CDH 5
• April 23, 2014 » Resource Management Fundamentals
• April 22, 2014 » NewSQL Vs. SQL on Hadoop
• April 22, 2014 » Deep Learning
• April 21, 2014 » Presto as a Service
• April 20, 2014 » Apache Hadoop YARN – Related Work
• April 19, 2014 » Advanced and Distributed Operating Systems
• April 18, 2014 » 10 Usability Heuristics for User Interface Design
• April 17, 2014 » Folder Management
• April 16, 2014 » Adding ACID to Apache Hive
• April 15, 2014 » Eight SQL on Hadoop Challenges
• April 15, 2014 » Computer Science @ University of Cambridge
• April 15, 2014 » 11 SQL-on-Hadoop Tools
• April 14, 2014 » Healthcare Does Hadoop
• April 14, 2014 » Bloom Filter
• April 13, 2014 » Processing streaming data in Hadoop with Apache Storm
• April 12, 2014 » Interactive Query for Hadoop with Apache Hive on Apache Tez
• April 12, 2014 » Introducing Apache Tez 0.4
• April 11, 2014 » How to Share a Bread Evenly
• April 10, 2014 » Big Data Genomics Sequencing
• April 9, 2014 » 24 Live Another Day
• April 9, 2014 » Using Gitlab on Mac OS X
• April 8, 2014 » Gitlab Installation on Mac OS X
• April 7, 2014 » Failures in YARN
• April 7, 2014 » Failures in Classic MapReduce
• April 6, 2014 » YARN Framework and Fault Tolerance
• April 5, 2014 » Smart Things vs. Many Experienced Things
• April 4, 2014 » Apache Hadoop YARN – Node Manager (NM)
• April 3, 2014 » Hardening Hadoop for Healthcare with Project Rhino
• April 3, 2014 » Apache Tajo
• April 3, 2014 » Build Instructions for Apache Tajo
• April 2, 2014 » Apache Hadoop YARN – Application Master (AM)
• April 2, 2014 » Apache Hadoop in 2013 - The State of the Platform
• April 1, 2014 » Grid Computing
• April 1, 2014 » Design Objectives of Computer Clusters
• April 1, 2014 » Clustering for Massive Parallelism

March

• March 31, 2014 » Apache Hadoop YARN – Architecture Overview
• March 31, 2014 » Apache Hadoop YARN – Resource Manager (RM)
• March 30, 2014 » Apache Hadoop YARN – History and Rationale, Shared Clusters
• March 30, 2014 » Functional Programming
• March 29, 2014 » Why Functional Programming?
• March 29, 2014 » Parallel Computing
• March 28, 2014 » Navier-Stokes Equations
• March 28, 2014 » Implementing Graph-Based Applications
• March 28, 2014 » Designing Graph-Based Applications
• March 27, 2014 » Depth of Knowledge
• March 27, 2014 » Data-intensive Computing
• March 26, 2014 » Mapping and Folding and the Map-Reduce Paradigm
• March 26, 2014 » Codd's 12 Rules
• March 25, 2014 » OLAP vs. OLTP
• March 25, 2014 » Network Topology and Hadoop
• March 25, 2014 » Comparison - Ad-hoc vs Stored Procedure vs Dynamic SQL
• March 24, 2014 » Ensuring the Validity, Veracity, and Volatility of Big Data
• March 24, 2014 » Steve Jobs at SIGGRAPH 1995
• March 24, 2014 » Operationalizing Big Data
• March 24, 2014 » Modern Oil & Gas Architectures Built with Hadoop
• March 23, 2014 » Using Avro in MapReduce Jobs with Pig
• March 23, 2014 » Using Avro in MapReduce Jobs with Java
• March 23, 2014 » Using Avro in MapReduce Jobs with Hive
• March 23, 2014 » Using Avro in MapReduce Jobs with Hadoop Streaming
• March 23, 2014 » MapReduce and Hadoop Papers in the VLDB
• March 23, 2014 » NoSQL Databases
• March 23, 2014 » MapReduce and Hadoop Algorithmic in Academic Papers
• March 22, 2014 » Visualization for Data-Intensive Science
• March 22, 2014 » Theory of Everything
• March 22, 2014 » Stanford Network Analysis Platform(SNAP)
• March 22, 2014 » Gray’s Laws Database-centric Computing in Science
• March 22, 2014 » Connecting to the Scientists
• March 21, 2014 » Big Data Dilemma
• March 21, 2014 » Conduct Research Survey
• March 20, 2014 » Polyglot Persistence
• March 20, 2014 » Functional versus Procedural Programming Models
• March 19, 2014 » The Data Science Process
• March 18, 2014 » Statistical Thinking in the Age of Big Data
• March 18, 2014 » Populations and Samples
• March 17, 2014 » Thought Experiment - Meta-Definition
• March 16, 2014 » A Data Science Profile
• March 15, 2014 » The Role of the Social Scientist in Data Science
• March 15, 2014 » What is Data Science? - The Current Landscape
• March 15, 2014 » Community Detection - Clustering Coefficient
• March 14, 2014 » What is Data Science?
• March 13, 2014 » Stream Data Processing for Performance Evaluation of the Equipment in an Offshore Plant
• March 12, 2014 » Hive on Tez
• March 12, 2014 » Functional Requirements of Hive on Tez Phase I
• March 12, 2014 » Query Planning of Hive on Tez
• March 12, 2014 » Design of Hive on Tez
• March 11, 2014 » Apache Tez 0.3 Released!
• March 10, 2014 » Macport Commands Summary
• March 8, 2014 » Predictive Methodologies - Analysis of Time and Space
• March 8, 2014 » Predictive Methodologies - Analysis of Space
• March 8, 2014 » Predictive Methodologies - Analysis of Social Networks
• March 7, 2014 » Theoretical Foundations of Data Mining and Predictive Analytics
• March 7, 2014 » Data Used in Predictive Policing
• March 6, 2014 » Operational Challenges of Predictive Policing
• March 6, 2014 » Forecast Vs. Prediction
• March 5, 2014 » Wiki Tutorial
• March 5, 2014 » Recommendations
• March 5, 2014 » Predictive Policing Myths and Pitfalls
• March 5, 2014 » Prediction-Led Policing Process and Prevention Methods
• March 5, 2014 » Facebook Presto
• March 5, 2014 » Apache Drill
• March 4, 2014 » Predictive Policing
• March 4, 2014 » A Taxonomy of Predictive Methods
• March 3, 2014 » Apache Hadoop YARN – History and Rationale
• March 3, 2014 » “Big Data” Promises a Revolution
• March 2, 2014 » As MapReduce fades, Apache Spark is now a top-level project
• March 1, 2014 » Apache Hadoop YARN – ResourceManager
• March 1, 2014 » Apache Hadoop YARN – Yet Another Resource Negotiator
• March 1, 2014 » Apache Hadoop YARN – NodeManager

February

• February 28, 2014 » Apache Hadoop YARN – Concepts and Applications
• February 28, 2014 » Apache Hadoop YARN – Background and Overview
• February 28, 2014 » Papers about MapReduce
• February 28, 2014 » Introducing Apache Hadoop YARN
• February 27, 2014 » T-Shaped Data Scientists
• February 27, 2014 » Chest aching Story
• February 26, 2014 » Adapting to Change
• February 25, 2014 » Agile Big Data
• February 24, 2014 » Scales of Big Data
• February 23, 2014 » The Variety of Data Scientists
• February 22, 2014 » The Real-Time Big Data Architecture (RTDBA) Stack
• February 22, 2014 » The Five Phases of Real Time
• February 22, 2014 » Case Studies of Analyzing Data
• February 21, 2014 » Like a star
• February 21, 2014 » FINDING INFORMATION ON THE WEB
• February 21, 2014 » Data Science, Engineering, and Data-Driven Decision Making
• February 21, 2014 » Clustering Data Scientists
• February 21, 2014 » Advanced Metasearch Engine Technology
• February 20, 2014 » PredictionIO
• February 18, 2014 » TDD Best practices
• February 17, 2014 » A Material Point Method For Snow Simulation
• February 17, 2014 » Test-Driven Development in a nutshell
• February 16, 2014 » Reflections on Image-Based Modeling and Rendering
• February 15, 2014 » Key Points from NoSQL Distilled
• February 11, 2014 » Scrum Events
• February 11, 2014 » Multi-tenant Database Systems
• February 11, 2014 » Big Data in Motion
• February 10, 2014 » Tez Design - Introduction
• February 10, 2014 » Introduction to the Maven
• February 9, 2014 » Building a Hybrid Modern Data Architecture for Apache Hadoop
• February 8, 2014 » Let it go
• February 7, 2014 » Continuous Quries Languages
• February 6, 2014 » Semantics of Relations in Continuous Queries
• February 5, 2014 » Randy Pausch Last Lecture, Achieving Your Childhood Dreams
• February 5, 2014 » Continuous Quries as Views
• February 4, 2014 » Native C/C++ Like Performance For Java Object Serialization
• February 4, 2014 » Building the Health Information Infrastructure for the Modern ePatient
• February 3, 2014 » Using ByteBuffer in Java
• February 3, 2014 » Sunflower
• February 2, 2014 » Solving the Wanamaker Problem for Healthcare

January

• January 28, 2014 » Continuous Query Semantics and Operators (Part II)
• January 28, 2014 » Effective Team Membership
• January 27, 2014 » Stream Windows
• January 27, 2014 » Continuous Query Semantics and Operators (Part I)
• January 27, 2014 » Parallel R
• January 26, 2014 » Writing Input And Output Adapters
• January 26, 2014 » Stream Models
• January 25, 2014 » Understanding the Types of Big Data Problems
• January 25, 2014 » Understanding Human Dynamics
• January 25, 2014 » A Flying Butterfly
• January 22, 2014 » Esper Relational Database Adapter
• January 21, 2014 » Event Rendering to XML and JSON
• January 21, 2014 » Esper Socket Adapter
• January 21, 2014 » Esper Adapter Concept
• January 20, 2014 » Confluent and Functional Persistence
• January 19, 2014 » Full Persistence
• January 18, 2014 » Partial Persistence
• January 17, 2014 » Persistent Data Structures
• January 16, 2014 » Writing a Tez Input, Processor and Output
• January 16, 2014 » Synchronization among Heterogeneous Distributed Objects
• January 16, 2014 » Runtime API in Apache Tez
• January 16, 2014 » Re-Using Containers in Apache Tez
• January 16, 2014 » Introducing Tez Sessions
• January 16, 2014 » Data Processing API in Apache Tez
• January 16, 2014 » Apache Tez Dynamic Graph Reconfiguration
• January 15, 2014 » Apache Tez A New Chapter in Hadoop Data Processing
• January 14, 2014 » Introduction to the Tez
• January 14, 2014 » How to write a good research paper
• January 13, 2014 » Principal Component Analysis
• January 12, 2014 » Data Stream Management
• January 11, 2014 » Scatter plots in Python
• January 11, 2014 » Generating random numbers and plots in Python
• January 11, 2014 » Physical Properties and selection of thermodynamic models
• January 11, 2014 » JUnit, A Tool for Test-Driven Development
• January 11, 2014 » Syntax highlighting tools for github page
• January 11, 2014 » Boxplots comparing two different populations in Python
• January 10, 2014 » Centrifugal Compressor Efficiency - Part 4
• January 10, 2014 » Centrifugal Compressor Efficiency - Part 3
• January 10, 2014 » Centrifugal Compressor Efficiency - Part 2
• January 10, 2014 » Centrifugal Compressor Efficiency - Part 1
• January 9, 2014 » In-Memory Caches
• January 9, 2014 » Pattern Matching Techniques
• January 8, 2014 » Sequence Diagram
• January 5, 2014 » Computational Thinking
• January 4, 2014 » Introduction to Transactional Memory
• January 4, 2014 » Monte-Carlo Methods An Introduction
• January 4, 2014 » Impressionist Tutorial
• January 4, 2014 » Introduction to Impress.js
• January 3, 2014 » PRODML Data Schema and API Specifications
• January 3, 2014 » The Invention of Stream Computing
• January 3, 2014 » Real-time Operational Intelligence
• January 3, 2014 » JAXB Class Generation From XML Schema File using JAXB Tool
• January 3, 2014 » Explaining Agile
• January 2, 2014 » Introduction to Esper for Java
• January 2, 2014 » The Emergence of NoSQL

2013

December

• December 27, 2013 » My Scoop It! Sites
• December 26, 2013 » Concurrent Bug Patterns and How to Test Them
• December 26, 2013 » Introduction to Bug Patterns in Java
• December 24, 2013 » How to overcome common obstacles to publishing in English
• December 24, 2013 » Real-Time Data Stream Manager (RTDSM) Interface Specification
• December 21, 2013 » Modelling in Big Data
• December 16, 2013 » Analyzing Data in Motion A Real-World View
• December 16, 2013 » Understanding trade-offs with Brewer’s CAP theorem
• December 14, 2013 » Foundational data architecture patterns
• December 14, 2013 » Applications using graph representation
• December 13, 2013 » N-Screen Application Development Manual
• December 12, 2013 » YARN (MapReduce 2)
• December 12, 2013 » Android WebView Application using Naver Open API
• December 11, 2013 » Stream Data Schema Design
• December 11, 2013 » Introduction to Stream Computing
• December 10, 2013 » Streams Application Design
• December 10, 2013 » Filter pattern
• December 9, 2013 » Analytics vs. Predictive Analytics
• December 9, 2013 » Streams design patterns
• December 9, 2013 » Publications
• December 9, 2013 » The evolution of analytics
• December 3, 2013 » Open The Door

November

• November 22, 2013 » Extreme Programming
• November 15, 2013 » Characteristics of the Smart Devices
• November 9, 2013 » Thermodynamics Basic Concepts

October

• October 15, 2013 » Scrum Agile Development Process
• October 6, 2013 » How to play the piano in a week
• October 5, 2013 » Smile Again

September

• September 25, 2013 » Agile Project Management
• September 15, 2013 » Logical Communication-based Middleware for Collaboration among Smart Apps in P2P Network Environments
• September 5, 2013 » VLDB 2013

August

• August 21, 2013 » Impedance Mismatch
• August 21, 2013 » The Value of Relational Databases

July

• July 22, 2013 » Agile Processes and Scrum
• July 12, 2013 » What is NoSQL?

June

• June 25, 2013 » Korean Computer Graphics Conference 2013
• June 22, 2013 » Neo4j
• June 21, 2013 » Graph Databases
• June 9, 2013 » NoSQL History

May

• May 21, 2013 » The Presentation Secrets of Steve Jobs

April

• April 15, 2013 » Paper Organization

February

• February 10, 2013 » Wisdom from Steve Jobs

2012

May

• May 10, 2012 » Git Commands

April

• April 10, 2012 » Git Concepts and Architecture

March

• March 8, 2012 » Adding a post to github page

---

comments powered by Disqus

---