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Lecture
Graph Coloring: Theory and Applications
Graph Chatbot
Related lectures (29)
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Graph Coloring II
Explores advanced graph coloring concepts, including planted coloring, rigidity threshold, and frozen variables in BP fixed points.
Belief Propagation for Graph Coloring
Explores Belief Propagation for graph coloring and its convergence properties.
Minimum Spanning Trees: Prim's Algorithm
Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.
Graph Algorithms II: Traversal and Paths
Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.
Density of States and Bayesian Inference in Computational Mathematics
Explores computing density of states and Bayesian inference using importance sampling, showcasing lower variance and parallelizability of the proposed method.
Graph Theory Basics
Introduces graph theory basics, Ramsey theory, and graph coloring concepts.
Reformulating Problems: Tools and Intuition
Focuses on open problems and the importance of reformulating problems with better tools and intuition.
Graphical Models: Probability Distributions and Factor Graphs
Covers graphical models for probability distributions and factor graphs representation.
Dynamic Programming: Shortest Paths Algorithms
Explores dynamic programming strategies for finding shortest paths in networks with various algorithms and complexities.
Graph Coloring: Basics and Applications
Covers the basics and applications of graph coloring, including balancing vectors and achieving perfect fairness.
