Primal-dual Methods for Composite Minimization

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Primal-dual Optimization II

Explores primal-dual optimization methods, focusing on Lagrangian approaches and various methods like penalty, augmented Lagrangian, and splitting techniques.

Solving Linear Programs: SIMPLEX Method

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Primal-dual Optimization: Lagrangian Methods

Explores primal-dual optimization with a focus on Lagrangian methods and their convergence, drawbacks, and enhancements.

Cones of convex sets

Explores optimization on convex sets, including KKT points and tangent cones.

Convex Optimization Problems: Standard Form

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Convex Optimization Problems: Theory and Applications

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Linear Optimization: Auxiliary Problem

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Convex Optimization: Exercises

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Adversarial Machine Learning: Theory and Applications

Covers the theory and applications of adversarial machine learning, focusing on minmax optimization and robustness to adversarial examples.