Computation & Algorithms I

Related lectures (22)

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Covers classical and quantum computational complexity concepts and implications.

Explores abductive reasoning, search algorithms, and heuristic search for problem-solving.

Explores double descent curves and overparametrization in machine learning models, highlighting the risks and benefits.

Covers basic algorithm ingredients, search algorithms, control structures, and algorithm correctness.

Covers search algorithms, focusing on abductive reasoning and heuristic search strategies.

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

Explores solving Connect Four using game theory algorithms and compares Alpha-Beta pruning with Monte-Carlo tree search.

Covers conditional branching in C++, focusing on if-else and switch-case statements, logical operators, and control structures.

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