Lectures related to Theory of Computation: Undecidable Problems

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

Explores countability and undecidable problems in the theory of computation.

Explores the theory of computability, decision problems, complexity classes, and the 'P vs. NP' conundrum.

Explores undecidability through recursive languages, Turing machines, and the halting problem.

Covers optimization algorithms, stable matching, and Big-O notation for algorithm efficiency.

Explores the unsolvability of the halting problem in algorithms and the limitations of procedures in determining program halting.

Covers recursively enumerable languages, Turing machines, and the construction of undecidable languages.

Explores linear search, insertion sort, coin change, maximum matching, and the halting problem in algorithms.

Delves into the theory of computation, covering decidability, complexity, P vs. NP, and reductions.

Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.

Covers coin rendering and the limitations of the greedy algorithm in finding optimal solutions.

Covers Dijkstra's algorithm and its application to the all-pairs shortest path problem.

Explores the theory of computation, emphasizing problems definition, counting, and the limits of algorithmic computation.

Introduces an improved algorithm for three-color parity games, focusing on progress measures, acceleration, and practical speed-up.

Explores algorithm correctness, worst-case complexity analysis, and efficiency comparison based on input size.

Explores the theory of computation, undecidable problems, complexity measurement, and the P complexity class.

Covers counting distinct elements using hash functions and the median trick.

Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.

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