Multi-arm Bandits

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Explores the transition from algorithms to programs through compilation, emphasizing constraints and machine-understandable coding practices.

Explores the coin change problem, comparing greedy and dynamic programming algorithms for optimal solutions.

Covers algorithms for searching, sorting, optimization, and the Halting Problem.

Covers the process of solving Linear Programs (LPs) using the simplex method.

Covers mathematical principles and algorithms of optimization, using real-world examples and Python implementation.

Explores optimization duality, weak and strong duality, practical optimization algorithms, and challenges in nonconvex-concave problems.

Explores dynamic programming for optimizing decision-making processes over time, using real-world examples like oil extraction and stock trading.

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

Introduces the CS-250 Algorithms course, covering its structure, objectives, and key topics in algorithmic problem-solving.

Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.