Lectures related to Bellman-Ford Algorithm: Shortest Path

Graph Algorithms II: Traversal and Paths

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.

Dijkstra's Algorithm Overview

Demonstrates the iterative process of applying Dijkstra's algorithm to find optimal paths.

Shortest Path Algorithms: BFS and Dijkstra

Explores Breadth-First Search and Dijkstra's algorithm for finding shortest paths in graphs.

Shortest Paths: Negative Weights

Explores Bellman-Ford algorithm for negative weight graphs and currency exchange rates.

Minimum Spanning Trees: Prim's Algorithm

Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.

Shortest Paths: Negative Weights & Applications

Covers Minimum Spanning Trees, Kruskal's Algorithm, and Shortest Paths in directed graphs.

Dynamic Programming: Shortest Paths Algorithms

Explores dynamic programming strategies for finding shortest paths in networks with various algorithms and complexities.

Dijkstra's Algorithm and Shortest Path

Covers Dijkstra's algorithm for shortest path problems and its application in ALL-TO-ONE and ALL-PAIRS algorithms.

Shortest Paths: Bellman-Ford and Dijkstra

Covers the Bellman-Ford and Dijkstra algorithms for finding shortest paths in graphs with different edge weights.

Bellman-Ford Algorithm: Shortest Path Estimation

Explains the Bellman-Ford algorithm for finding the shortest path in a directed graph with edge weights.

Prim's and Kruskal's Algorithms

Explores Prim's and Kruskal's algorithms for finding minimum spanning trees in a graph, covering their correctness, implementation, and analysis.

Unweighted Bipartite Matching

Introduces unweighted bipartite matching and its solution using linear programming and the simplex method.

Bellman-Ford Algorithm: Analysis and Correctness

Explores the Bellman-Ford algorithm, its correctness, and practical applications in dynamic networks and real-world scenarios.

Networked Control Systems: Opportunities

Explores coordination in networked control systems, graph theory, and consensus algorithms.

Minimum Guardians in Graphs

Explores the concept of minimizing guardians in graphs through strategic edge selection.

Message passing in graphical models

Explains message passing in graphical models and the matching problem in graph theory.

Dynamic Programming: Pascal's Triangle & Floyd's Algorithm

Explores dynamic programming through Pascal's Triangle and Floyd's Algorithm.

Sparsest Cut: ARV Theorem

Covers the proof of the Bourgain's ARV Theorem, focusing on the finite set of points in a semi-metric space and the application of the ARV algorithm to find the sparsest cut in a graph.

Graph Theory and Network Flows

Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.

Dijkstra's Algorithm and Probabilistic Analysis

Introduces Dijkstra's algorithm and probabilistic analysis through the Hiring Problem.