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Tutorial - Algorithms for Sparse Optimization and Machine Learning
Tutorial - Algorithms for Sparse Optimization and Machine Learning
Stochastic-gradient, Coordinate Descent, and Newton€™s Method
Optimization Taxonomy and Mathematical Foundations
Optimization: Recognizing Solutions and Algorithmic Basics
Optimization, Learning, and Processes
Optimization in Machine Learning and Data Analysis
Optimality, Duality, and Complementarity for Constrained Optimization
Linear Programming Part II: Interior-point Methods and Extensions to Convex Quadratic Programming and Linear Complementarity
Linear Programming Part I: Duality Theorem and Simplex Method
Interior-Point and Augmented Lagrangian Algorithms for Optimization and Control
First-order Methods: Convex and Nonconvex Problems - Unconstrained, Constrained, and Regularized Problems
Constrained Nonlinear Optimization Theory