These lecture notes will be updated frequently, and may contain typographical or even factual errors.
Gradient methods (unconstrained problems) (last updated: 09/05)
Gradient methods (constrained problems) (last updated: 09/12)
Subgradient methods (last updated: 9/21)
Mirror descent (last updated: 10/3)
Proximal gradient methods (last updated: 10/9)
Accelerated gradient methods (last updated: 10/31)
Smoothing for nonsmooth optimization (last updated: 11/5)
Dual and primal-dual methods (last updated: 11/6)
Alternating direction method of multipliers (ADMM) (last updated: 11/6)
Stochastic gradient methods (last updated: 11/16)
Variance reduction for stochastic optimization (last updated: 11/16)
Quasi-Newton methods (last updated: 11/6)
Nonconvex optimization for statistical estimation (Part 1)(Part 2) (last updated: 11/30)