Homework 3 (due 4/25). Exercises A2.3, A2.5, A2.17, A2.20 (b,c), A2.21, A3.27. Problem A3.27 requires the file affine_pol_data.m.
Homework 4 (due 5/2). Exercises T4.29, A3.21, A3.11, A5.9, A7.9.
Homework 5 (due 5/9). Exercises A3.13, T5.11, A4.3, T5.21 (a,b,c), A4.14 and an additional problem.
Homework 6 (due 5/16). Exercises T5.26, A4.20, A4.10, A4.17, A12.12, A5.4.
Homework 7 (due 5/23). Exercises A4.6, T5.29, A6.1, T7.4, A6.5, A7.1. Problem A6.5 requires the file nonlin_meas_data.m.
Homework 8 (due 5/30). Exercises A8.1, A8.6. Exercise A8.6 requires the file approx_tv_denoising_data.m.
Homework solutions and grades are posted on the EEweb course website. (Follow the links to “Assignments” or “Grades”.)
Lectures: Boelter 5440. Tuesday & Thursday 12:00-1:50PM.
Textbook The textbook is Convex Optimization, available online and in hard copy at the UCLA bookstore. The following books are useful as (optional) reference texts.
A. Ben-Tal and A. Nemirovski, Lectures on Modern Convex Optimization (SIAM).
D. Bertsekas, A. Nedic, A.E. Ozdaglar, Convex Analysis and Optimization (Athena Scientific).
D. Bertsekas, Convex Optimization Theory (Athena Scientific).
J. M. Borwein and A. S. Lewis, Convex Analysis and Nonlinear Optimization (Springer).
J.B. Hiriart-Urruty and C. Lemarechal, Convex Analysis and Minimization Algorithms (Springer).
D. Luenberger and Y. Ye, Linear and Nonlinear Programming (Springer).
Y. Nesterov, Introductory Lectures on Convex Optimization: A Basic Course (Kluwer).
J. Nocedal and S. Wright, Numerical Optimization (Springer).
Course requirements. Weekly homework assignments; open-book final exam on Wednesday, June 12, 11:30-2:30PM. The weights in the final grade are: homework 20%, final exam 80%.
Software. We will use CVX, a MATLAB software package for convex optimization.