Lecture
Computational Complexity: Theory and Applications
Related lectures (90)
Max-Flow Min-Cut
Explores the Ford Fulkerson algorithm, Max-Flow Min-Cut theorem, Incidence matrix, and network optimization complexity.
Linear Programming: Optimization and Constraints
Explores linear programming optimization with constraints, Dijkstra's algorithm, and LP formulations for finding feasible solutions.
Integer Program Formulation
Covers the process of formulating integer programs and improving solutions.
Dijkstra's Algorithm: All-Pairs
Covers Dijkstra's algorithm and its application to the all-pairs shortest path problem.
Complex Systems: Critical Phenomena
Explores critical phenomena in complex systems, including stochastic objects, percolation, and combinatorial optimization.
Optimization Algorithms
Covers optimization algorithms, convergence properties, and time complexity of sequences and functions.
Integer Programming Basics
Introduces the basics of integer programming, including binary integer programs and constraint strategies.
Solving Parity Games in Practice
Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.
Reformulating Problems: Tools and Intuition
Focuses on open problems and the importance of reformulating problems with better tools and intuition.
Metropolis-Hastings Algorithm
Covers the Metropolis-Hastings and Glauber algorithms for sampling from the Boltzmann distribution in the Curie-Weiss model.