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Lecture
Graph Theory Basics
Graph Chatbot
Related lectures (33)
Minimum Spanning Trees: Prim's Algorithm
Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.
Graph Theory Fundamentals
Covers the fundamentals of graph theory, including vertices, edges, degrees, walks, connected graphs, cycles, and trees, with a focus on the number of edges in a tree.
Graph Algorithms II: Traversal and Paths
Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.
Minimal Spanning Tree
Covers the concept of weighted graphs and the Greedy algorithm for finding a minimal spanning tree.
Networked Control Systems: Opportunities
Explores coordination in networked control systems, graph theory, and consensus algorithms.
Networks: Trees
MOOC: Optimization: principles and algorithms - Network and discrete optimization
Explains the concept of trees in graph theory and the definition of a spanning tree.
Linear Programming Duality
Covers linear programming duality and complementary slackness condition.
Knowledge Inference for Graphs
Explores knowledge inference for graphs, discussing label propagation, optimization objectives, and probabilistic behavior.
Shortest Path Algorithms: BFS and Dijkstra
Explores Breadth-First Search and Dijkstra's algorithm for finding shortest paths in graphs.
Graphical Models: Representing Probabilistic Distributions
Covers graphical models for probabilistic distributions using graphs, nodes, and edges.
Belief Propagation
Explores Belief Propagation in graphical models, factor graphs, spin glass examples, Boltzmann distributions, and graph coloring properties.
Networked Control Systems: Properties and Connectivity
Explores properties of matrices, irreducibility, and graph connectivity in networked control systems.
Connectivity in Graph Theory
Covers the fundamentals of connectivity in graph theory, including paths, cycles, and spanning trees.
Networked Control Systems: Graph Theory and Stochastic Matrices
Explores graph theory, stochastic matrices, consensus algorithms, and spectral properties in networked control systems.
Graph Coloring: Random vs Symmetrical
Compares random and symmetrical graph coloring in terms of cluster colorability and equilibrium.
Spanning Trees: Definition and Applications
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Introduces spanning trees in graphs and the Minimum Spanning Tree problem, exploring efficient algorithms for optimal decision-making.
Graph Theory and Network Flows
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Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.
Relations Between Events
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Explores relations between events, disjunctive constraints, and modeling with binary variables in optimization problems.
Interlacing Families and Ramanujan Graphs
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Explores interlacing families, Ramanujan graphs, and their construction using signed adjacency matrices.
Expander Graphs: Properties and Eigenvalues
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Explores expanders, Ramanujan graphs, eigenvalues, Laplacian matrices, and spectral properties.
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