COURSE DESCRIPTION

Syllabus on Brightspace

NOTES (updated on Sep 23)

Reference Books (for those with *, online access available via Purdue Library):

Amir Beck, Introduction to Nonlinear Optimization*
Amir Beck, First order methods in optimization*
Jorge Nocedal and Stephen J. Wright, Numerical Optimization*
Yurii Nesterov, Introductory Lectures on Convex Optimization A Basic Course*
Ernest K. Ryu and Wotao Yin, Large-Scale Convex Optimization: Algorithms & Analyses via Monotone Operators*
Nicolas Boumal, An introduction to optimization on smooth manifolds

Note: The schedule is subject to change. Check back for changes and updates. Lecture notes will be posted here.

Week	Dates	Lecture Notes
1	08/24	Part I Smooth problems Introduction Lecture 1
	08/26	Lecture 2
	08/28	Lecture 3
2	08/31	Lecture 4
	09/02	Lecture 5
	09/04	Lecture 6
3	09/07	Labor Day. No Class.
	09/09	Lecture 7
	09/11	Part II Nonsmooth problems Lecture 8
4	09/14	Lecture 9
	09/16	Lecture 10
	09/18	Lecture 11
5	09/21	Lecture 12
	09/23	Lecture 13
	09/25	Lecture 14
6	09/28	Lecture 15
	09/30	Lecture 16
	10/02	Lecture 17
7	10/05	Lecture 18
	10/07	Lecture 19
	10/09	Part III Randomized algorithms Lecture 20
8	10/12	October Break. No Class.
	10/14
	10/16	In Class Quiz Date
9	10/19
	10/21	No In Person Class Watch Zoom Recording on Brightspace
	10/23
10	10/26
	10/28
	10/30
11	11/02
	11/04
	11/06	Part IV Riemannian optimization
12	11/09
	11/11
	11/13
13	11/16
	11/18
	11/20
14	11/23
	11/25	Thanksgiving. No Class.
	11/27	Thanksgiving. No Class.
15	11/30
	12/02	Part V Convergence for nonconvex problems
	12/04
16	12/07
	12/09
	12/11
17	12/14	Final Exam Week. No Class.
	12/16
	12/18