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Related lectures (28)

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Convex Optimization: Convex Functions

Covers the concept of convex functions and their applications in optimization problems.

Conjugate Duality: Understanding Convex Optimization

Explores conjugate duality in convex optimization, covering weak and supporting hyperplanes, subgradients, duality gap, and strong duality conditions.

Lagrangian Duality: Convex Optimization

Explores Lagrangian duality in convex optimization, transforming problems into min-max formulations and discussing the significance of dual solutions.

Optimization Methods: Convergence and Trade-offs

Covers optimization methods, convergence guarantees, trade-offs, and variance reduction techniques in numerical optimization.

Optimal Transport: Rockafellar Theorem

Explores the Rockafellar Theorem in optimal transport, focusing on c-cyclical monotonicity and convex functions.

Convexifying Nonconvex Problems: MGT-418 Lecture

Explores convexifying nonconvex problems through kernel tricks, sensitivity interpretation, and nonlinear dimensionality reduction.

Proximal and Subgradient Descent: Optimization Techniques

Discusses proximal and subgradient descent methods for optimization in machine learning.

Optimization in Networks

Explores duality in network optimization problems with examples and step-by-step explanations.