Lectures related to Max Sum Diversification

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

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

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

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

Explores dynamic programming for the Knapsack problem, discussing strategies, algorithms, NP-hardness, and time complexity analysis.

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

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

Introduces the concept of shortest path, discussing weighted paths, Hamiltonian paths, and path optimization algorithms.

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

Explores nonconvex optimization challenges and strategies, including blind image deconvolution and SDP relaxations.

Focuses on open problems and the importance of reformulating problems with better tools and intuition.

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

Explores Semidefinite Programming formulations, SDP relaxations, and optimization strategies with convergence guarantees.

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

Covers the concept of graph sketching with a focus on connected components.

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

Covers the basics of information theory, entropy, and fixed points in graph colorings and the Ising model.

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.

Explores a variety of open problems in graph theory and computational complexity, challenging students to analyze and solve complex issues.

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