FPTAS for Knapsack

Related lectures (28)

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

Covers bidding strategies, Game Theory, Nash equilibrium, system security, ancillary services, and market power in power systems.

Explains compression and Kraft inequality in codes and sequences.

Covers Projected Gradient Descent and Quadratic Penalty methods for optimization problems.

Explores the correctness and soundness of the Qubit Test, emphasizing probabilistic algorithms, trapdoors, and function inversion.

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

Explores the theory and application of quadrature formulas for numerical analysis.

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

Explains thermodynamic properties, equations of state, and mixture rules for energy systems modeling.

Covers the Runge-Kutta method for approximating solutions of differential equations.