Papers

Graph Learning

Surveys

Machine Learning on Graphs: A Model and Comprehensive Taxonomy

Classical Approach of Node Embedding

Combinatorial Optimization using Machine Learning

Surveys

Combinatorial Optimization and Reasoning with Graph Neural Networks

Machine Learning for Combinatorial Optimization: a Methodological Tour d’Horizon

GRAPH MINING

k-core decoposition (distributed direction)

1. Distributed k-core Decomposition

2. A distributed k-core Decomposition on Spark

3. kcoreTheoriesAndApplications

4. Parallel and Streaming Algorithms for K-Core Decomposition

Community Search

1. A SURVEY: survey of community search over big graph

Number Partition

1. Optimal Multi-Way Number Partitioning
2. Bounds on Multiprocessing Timing Anomalies SIAM

Graph Partition

1. balancedGraphPartition(Classic)
2. Streaming Graph Partitioning: An Experimental Study
3. Streaming Balanced Graph Partitioning Algorithms for Random
4. A Study of Partitioning Policies for Graph Analytics on Large-scale Distributed Platforms
5. Dynamic Scaling for Parallel Graph Computations
6. PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs
7. A survey of partition papers blog
8. HDRF: Stream-Based Partitioning for Power-Law Graphs
9. Windows-based Streaming Partitioning Algorithm(A very good example of windows based method)

Algorithm over large graph

PageRank

1. Realtime Top-k Personalized PageRank over Large Graphs on GPUs

K-core Decomposition

1. An Experimental Comparison of Partitioning Strategies in Distributed Graph Processing(metioned in 3.3)
2. Slides from Uwaterloo about graph partition
3. Efficient Core Decomposition in Massive Networks

My

ITAM-24:Intelligent Assistant Medical Diagnosis Based on Online Interactive Information

Gini Methodology Appllied to Macroeconomics Forecasting

Books

Algebra & Basic Maths

Matrix Computation

1. Matrix Cookbook
2. Old and New Matrix Algebra Useful for Statistics

Algorithms

1. Algorithms by Jeff Ericson

2. Parallel Algorithms CMU

Computer Archs

Prob & Stats

The Elements of Statistical Learning

Programming Languages

Graph & Network Science

1. Graph Representation Learning