Complexity Classes: Introduction and Examples

Related lectures (26)

Page 1 of 3

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

Covers classical and quantum computational complexity concepts and implications.

Introduces computational complexity, decision problems, quantum complexity, and probabilistic algorithms, including NP-hard and NP-complete problems.

Explores complexity classes P and NP, highlighting solvable and verifiable problems, including NP-complete challenges.

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

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

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

Explores critical phenomena in complex systems, including stochastic objects, percolation, and combinatorial optimization.

Explores algorithm complexity, big-O notation, induction, recursion, and analysis of running times, covering NP problems and complexity classes.

Covers the basics of algorithms, problem-solving, and efficient resolution methods.