CSE 203B, Winter 2021Convex OptimizationUniversity of California, San Diego

Instructor

- CK Cheng, room CSE2130, email: ckcheng+203B@ucsd.edu, tel: 858 534-6184
- Office hour: TBA
Teaching Assistant

- Chester Holtz, chholtz@ucsd.edu, ID : 797 963 2208
- Po-Ya Hsu, p8hsu@ucsd.edu
- James Liu, til002@ucsd.edu
- Office hours: TBA
Discussion Forum

- TBA
Schedule

- Lectures: 2:00-3:20PM TTH, zoom
- Discussion: 2:00-2:50AM F, zoom
References

- 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.
- Funcions of Matrices: Theory and Computation, N.J. Higham, SIAM, 2008.
- Fall 2016, Convex Optimization by R. Tibshirani, http://www.stat.cmu.edu/~ryantibs/convexopt/
- EE364a: Convex Optimization I, S. Boyd, http://stanford.edu/class/ee364a/
PrerequisiteBasic knowledge of numerical methods or intention of conducting projects related to scientific computation.

ContentWe study the formulations and algorithms solving convex optimization problems. The topics include convex sets, functions, optimality conditions, duality concepts, 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 pptx, pdf, and slides with notes on W1A pdf.
- Lecture 1 survey on grading policy: 50% HW, 25% Midterm, 25% project
- Lecture 2 Convex Set pptx, pdf, slides with notes on W1B pdf, slides with notes on W2A1 pdf, slides with notes on W2A2 pdf, notes on W2B pdf.
- Lecture 3 Convex Function pptx, pdf, slides with notes on W3A pdf, slides with notes on W3B pdf, slides with notes on W4A pdf.
- Lecture 4 Formulation pptx, pdf, slides with notes on W4B pdf, slides with notes on W5A pdf.
- Lecture 5 Duality pptx, pdf, slides with notes on W5B pdf, slides with notes on W6A pdf, slides with notes on W6B pdf, slides with notes on W7B pdf, slides with notes on W8A pdf, slides with notes on W8B pdf.
- Part II: Algorithms

- Lecture 9 Unconstrained Minimization pptx, pdf, slides with notes on W8B pdf, slides with notes on W9A pdf.
- Lecture 10 Equality Constrained Minimization pptx, pdf, slides with notes on W9B pdf, slides with notes on W10A pdf.
- Lecture 11 Interior Point Methods pptx, pdf, slides with notes on W10B pdf.
Homework

- Policy for late homework: 10% discount for each day
- Homework 0: Linear Algebra tex, pdf, due 1/18/2021 (problem 2.4 updated on 1/11/2021).
- Homework 1: Convex Set tex, pdf, due 1/25/2021, solution: pdf
- Homework 2: Convex Function tex, pdf, due 2/1/2021, solution: pdf
- Homework 3: Problem Formulation, HW3 tex file tex, figure ellipsoid.png, and data hw3_signal_noise.txt, HW3 pdf, due 2/8/2021, solution: pdf
- Homework 4: Duality tex, pdf, due 2/15/2021
Discussion

- Discussion 1: Linear Algebra Review: pdf. tex.
- Discussion : Convex Sets: pdf
- Discussion : Convex Functions 1: pdf
- Discussion : Convex Functions 2: pdf
- Discussion : Convex Formulation: pdf
- Discussion : Midterm Review: pdf
Exam

- Winter 2021 Midterm Exam: tex, pdf, and solution: pdf. Take home exam posted on 10AM Tu 2/16, due 10AM Th 2/18. No class lecture on Tu 2/16.
- Fall 2017 Midterm review, pdf file
- Fall 2017 Midterm Rubrics, pdf file
- Winter 2019 Midterm Rubrics, pdf file
- Winter 2020 Midterm, pdf file, tex file.
- Winter 2020 Midterm Solution, pdf file.
ProjectWinter 2021: Two Award Winning Projects Project Outlines due Monday March 1, 2021 pdf, pptx. Clarification of the project outlines and report (what are we looking for?) pdf, pptx. Outline Sample: Market Forcast docx Outline Sample: Spectralization pdf Outline Sample: ImageSeg pdf Final Presentation Sample pdf Final Report Sample: Market Forcast pdf Report Sample: Sprectralization pdf Report Sample: ImageSeg pdf Two award winning teams of the Best Presentation Winter 2019 Award.jpg.