Separating Hyperplanes: Theory and Applications

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Page 3 of 4

Covers Markov games, their dynamics, equilibria, and applications in reinforcement learning.

Explores Markov's theorem, Chernoff bound, and probability theory fundamentals, including good coloring, 2-colorable graphs, and rare events.

Focuses on open problems and the importance of reformulating problems with better tools and intuition.

Explores convex sets, their properties, and applications in optimization.

Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.

Covers zero-sum games, focusing on Nash equilibria, security strategies, and their applications in various scenarios.

Covers thermodynamic concepts and exam questions from 2012, 2013, and 2015.

Explains the SIMPLEX method for solving linear programs and optimizing the solution through basis variable manipulation.

Explores constraints, efficiency, and complexity in linear algebra, emphasizing convexity and worst-case complexity in algorithm analysis.

Explores the Poisson Paradigm and dependency measures in ordered pairs and graphs.