Computational Complexity: Theory and Applications

Related lectures (29)

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Covers the basics of computational complexity, including big O notation and complexity classes.

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

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

Delves into complexity theory, focusing on the P vs NP problem and the classification of computational problems based on efficiency.

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

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

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

Explores cryptanalysis in public-key systems and the power of interaction in interactive proofs, covering CO-NP, NP classes, P vs. NP, and more.

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

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