Optimization
Mathematical optimization — convex, combinatorial, and numerical.
Convex optimization, gradient-based methods, constrained optimization, and combinatorial optimization.
Documents
Notes
- First-Order Methods for Constrained Optimization
- Descent Methods and Momentum
- Differentiation, Adjoints, and Automatic Differentiation
- Duality and Lagrangian Methods
- Foundations of Smooth Optimization
- Introduction to Optimization for Data Analysis
- Nonsmooth Optimization — Subgradients and Proximal Methods
- Stochastic Gradient and Coordinate Descent