Concept

Degeneracy (graph theory)

Related lectures (25)

Explores advanced graph coloring concepts, including planted coloring, rigidity threshold, and frozen variables in BP fixed points.

Graph Coloring III

Explores properties of clusters and colorability threshold in graph coloring, including average connectivity and rigidity.

Graph Coloring: Random vs Symmetrical

Compares random and symmetrical graph coloring in terms of cluster colorability and equilibrium.

Statistical Physics of Clusters

Explores the statistical physics of clusters, focusing on complexity and equilibrium behavior.

Graph Coloring: Basics and Applications

Covers the basics and applications of graph coloring, including balancing vectors and achieving perfect fairness.

Graph Coloring: Theory and Applications

Covers the theory and applications of graph coloring, focusing on disassortative stochastic block models and planted coloring.

Dynamic Programming: Fibonacci Numbers

Explores dynamic programming with Fibonacci numbers, greedy coin change algorithms, graph coloring, and knapsack variants.

Cluster Complexity Analysis

Covers the analysis of cluster complexity in random graph coloring.

Low Diameter Random Partitioning

Discusses Low Diameter Randomized Decomposition and graph partitioning for edge cuts and coloring.

Graph Coloring: Entropy and Free Energy

Explains entropy and free energy computation in graph coloring.

Independence Polynomial of Dependency Graph

Covers the independence polynomial of a dependency graph and related concepts such as graph coloring and directed graph properties.

Statistical Physics for Optimization & Learning

Covers statistical physics tools for optimization, learning, graph coloring, recommendation systems, and neural networks.

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Belief Propagation for Graph Coloring

Explores Belief Propagation for graph coloring and its convergence properties.

Belief Propagation on Graphs

Covers belief propagation on graphs, exploring computation challenges and heuristics, focusing on sparse random graphs' loop properties.

Graph Models and Brain Connectomics

Explores graph theory in brain connectomics, MRI applications, network analysis relevance, and individual fingerprinting.

Covers register allocation techniques and strategies, including graph coloring and spilling integration.

Ramsey Theory: Alterations and Colorings

Explores Ramsey theory, alterations, colorings in graphs, monochromatic matchings, and the significance of large cliques.

Graph Coloring and Directed Cycles

Explores graph coloring, directed cycles, LLL algorithm applications, and element dependencies in graphs.

Algorithmic Paradigms for Dynamic Graph Problems

Covers algorithmic paradigms for dynamic graph problems, including dynamic connectivity, expander decomposition, and local clustering, breaking barriers in k-vertex connectivity problems.