Optimization

Optimization covers methods to minimize (or maximize) an objective function, with or without constraints — the foundation of regression, machine learning, and portfolio allocation.

Detailed pages

Topic	Content
Convex optimization	Convex problems, KKT, Lagrange, duality, LP/QP
Gradient descent	GD, SGD, momentum, learning rate, convergence

Coming soon

Newton and quasi-Newton
Regularization
Quadratic optimization
Portfolio optimization
Ill-conditioned problems