Multi-arm Bandits

Related lectures (32)

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Covers optimization algorithms, focusing on Proximal Gradient Descent and its variations.

Discusses variance reduction techniques in stochastic simulation, focusing on allocation strategies and replica generation algorithms.

Covers gradient line search methods and optimization techniques with an emphasis on Wolfe conditions and positive definiteness.

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Explores the ingredients and selection of algorithms for different goals.

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

Explores the integrality gap concept in set cover and multiplicative weights algorithms.

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

Explores challenges in minimizing job completion time in distributed computing, focusing on data skew impact and efficient processing.

Explores dataflow analysis for optimization, including equations solving, live variables, reaching definitions, and very busy expressions.