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Hedging for LPs
Graph Chatbot
Related lectures (29)
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Approximation Algorithms
Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Generalization Error
Explores generalization error in machine learning, focusing on data distribution and hypothesis impact.
Sparsest Cut: Bourgain's Theorem
Explores Bourgain's theorem on sparsest cut in graphs, emphasizing semimetrics and cut optimization.
Distributions and Derivatives
Covers distributions, derivatives, convergence, and continuity criteria in function spaces.
Sparsest Cut: ARV Theorem
Covers the proof of the Bourgain's ARV Theorem, focusing on the finite set of points in a semi-metric space and the application of the ARV algorithm to find the sparsest cut in a graph.
Caratheodory Bounds: Integer Programming
Covers Caratheodory bounds for integer programming, focusing on linear programming and the existence of optimal solutions.
Sparsest Cut: Leighton-Rao Algorithm
Covers the Leighton-Rao algorithm for finding the sparsest cut in a graph, focusing on its steps and theoretical foundations.
Exponential Family: Maximum Entropy Distributions
Covers exponential families and maximum entropy distributions under moment constraints.
Semi-Definite Programming
Covers semi-definite programming and optimization over positive semidefinite cones.
Stable Laws and Limit Theorems
Explores stable laws, limit theorems, and random variable properties.
