Schedule

The schedule more than a week in advance is tentative.

Date	Topics	References
Jan 8	video lecture course overview	BV† Ch 1, Course overview slides
Jan 13, 15	convex sets	BV Ch 2, Convex sets slides
Jan 22, 27	convex functions	BV Ch 3, Convex functions slides, Matrix concentration notes
Jan 29	subgradients, optimal data mixing (project idea)	Subgradients slides, Optimal data mixing slides, Subgradient notes from Stanford's EE 364b
Feb 3, 5	video lecture convex optimization problems	BV Ch 4, Convex optimization problems slides
Feb 10, 12, 17	video lecture duality	BV Ch 5, Duality slides, Minimax notes, Optimality conditions notes
Feb 19	approximation and fitting problems	BV Ch 7, Approximation and fitting slides
Feb 24	statistical problems	BV Ch 8, Statistical problems slides, Minimum distance estimation notes, Entropy maximization notes
Feb 26	robust optimization	Robust optimization slides, Robust optimization notes, BV Appendix B (on the $S$-lemma)
Mar 10	gradient descent	Gradient descent slides, Gradient descent proofs
Mar 12	simply constrained optimization	Simply constrained optimization slides, Simply constrained optimization proofs,
Mar 17	subgradient descent	Subgradient descent slides, Subgradient descent proofs
Mar 19, 24	proximal map, proximal gradient descent	Proximal gradient descent slides, Proximal gradient descent proofs
Mar 26	(Nesterov) smoothing, proximal point method, extragradient method	Smoothing slides, Smoothing proofs
Mar 31, Apr 2	video lecture accelerated first-order methods	Accelerated gradient methods slides, Accelerated gradient methods proofs
Apr 7	dual methods, Fenchel duality	Dual methods slides
Apr 9	video lecture ADMM lecture video	ADMM slides
Apr 14	video lectures stochastic optimization, variance reduction	Stochastic optimization slides, Variance reduction slides, Stochastic optimization proofs
Apr 16, 21	perturbation of optimization problems	Perturbation of optimization problems notes

†BV refers to Boyd and Vandenberghe’s book on convex optimization.