CSE 203B, Winter 2023
University of California, San Diego
Instructor (Office hours TBA in Piazza)
Teaching Assistant (Office hours TBA in Piazza)
- CK Cheng, room CSE2130, email: ckcheng+203B@ucsd.edu, tel: 858 534-6184
- Chen, Danlu, email:email@example.com
- Giri, Vijay, email:firstname.lastname@example.org
- Holtz, Chester, email:email@example.com (Lead TA)
- Magee, Lucas, email:firstname.lastname@example.org
- Singh, Abhishek, email:email@example.com
- Song, Meng, email:firstname.lastname@example.org
- UCSD Podcast of lectures and discussion sessions
- Lectures: 12:30-1:50PM TTH, SOLIS 107
- Discussion: 4:00-4:50PM F, WLH 2001
- Convex Optimization, S. Boyd and L. Vandenberghe, Cambridge, 2004 (required textbook).
- Numerical Recipes: The Art of Scientific Computing, Third Edition, W.H. Press, S.A. Teukolsky, W.T. Vetterling, and B.P. Flannery, Cambridge University Press, 2007 (Recomended Reference)
- Matrix Computations, 4th Edition, G.H. Golub and C.F. Van Loan, Johns Hopkins, 2013 (Recommended Reference)
- Convex Optimization by R. Tibshirani, http://www.stat.cmu.edu/~ryantibs/convexopt/ (related resources)
- EE364a: Convex Optimization I, http://stanford.edu/class/ee364a/ (related resources)
- https://cseweb.ucsd.edu/~kuan/ (CSE203B notes in previous quarters)
Linear algebra and basic knowledge of numerical methods, or intention of conducting projects related to scientific computation.Content
We study the formulations and algorithms solving convex optimization problems. The topics include convex sets, functions, optimality conditions, duality concepts. If time permits, we will talk about gradient descent, conjugate gradient, interior-point methods, and applications. The objective of the course is to provide students the background and techniques for scientific computing and system optimization.Lectures
- Part I: Theory
- Lecture 1 Introduction, Class Logistics, Reading assignment: Chapter 1, Lecture slides pptx, pdf.
- Lecture 2 Convex Sets, Reading assignment: Chapter 2, Lecture slides pptx, pdf.
- Lecture 3 Convex Functions, Reading assignment: Chapter 3, Lecture slides pptx, pdf.
- Lecture 4 Formula, Reading assignment: Chapter 4, Lecture slides pptx, pdf, slides with notes Week-4A pdf, slides with notes Week-4B pdf.
- Lecture 5 Duality, Reading assignment: Chapter 5, Lecture slides pptx, pdf.
- Part II: Algorithms
Homework: gradescope submission
- Homework 1, Due 1/18/2023, pdf, tex.
- Homework 2, Due 1/25/2023, pdf, tex.
- Homework 3, Due date shifted to 2/8/2023, note that HW was revised 1/30/2023 pdf, tex.
- W1 Discussion (Slides)
- W2 Discussion (Slides)
- W3 Discussion (Slides)
- W4 Discussion (Slides)
- W5 Discussion
- W6 Discussion
- W7 Discussion
- Take-home exam 2/26-27/2023 (W7-8)