Clustering de Graphes

(à venir)

Lectures

• Basic models and questions in statistical network analysis

• Trinity: A Distributed Graph Engine on a Memory Cloud

• Dimensionality Reduction for Spectral Clustering

• Compressive Spectral Clustering

• Spectral Clustering on a Budget

• Partitioning Well-Clustered Graphs: Spectral Clustering Works!

• Bipartite Correlation Clustering: Maximizing Agreements

• Correlation Clustering and Biclustering with Locally Bounded Errors

• A Unified Framework for Model-based Clustering

• A Tensor Approach to Learning Mixed Membership Community Models

• Clustering from General Pairwise Observations with Applications to Time-varying Graphs

• A Spectral Algorithm with Additive Clustering for the Recovery of Overlapping Communities in Networks

• A Unified Framework for Structured Graph Learning via Spectral Constraints

• Path-Based Spectral Clustering: Guarantees, Robustness to Outliers, and Fast Algorithms

Lectures - métriques

• Social Clicks: What and Who Gets Read on Twitter?

Lectures Ranking

• CoSimRank

• PageRank

• A Local Spectral Method for Graphs: With Applications to Improving Graph Partitions and Exploring Data Graphs Locally

Modules

• networkx

• neo4j, py2neo, neo4j-python-driver

• snap.py

• GraKeL : algorithmes sur les graphes, plus court chemin, marches aléatoires, méthodes à noyaux

• scikit-network : de nombreux algorithmes comme PageRank, Louvain, …