Prof. L. Vandenberghe, UCLA

Exercise numbers with prefix ’T’ refer to the textbook. Exercise numbers with prefix ’A’ refer to the collection of additional exercises (last revised on 1/17).

Homework 1 (due

**Friday**1/20). Exercises T2.7, T2.12 (d,e,g), T2.16, and two additional problems. The additional problems requires the MATLAB files`circlefit.m`and`illumdata.m`.

Note the typo in T2.16: should be .Homework 2 (due Thursday 1/26). Exercises T2.37 (b,c), T3.1, T3.2, A2.10, A5.8. Problem A5.8 requires the files

`spline_data.m`and`bsplines.m`.Homework 3 (due Thursday 2/2). Exercises T3.18 (a), T3.19 (a), T3.22(c), A2.5 (a,b), A2.30, A2.31, A3.17.

Homework 4 (due Thursday 2/9). Exercises T3.55, A3.5, T4.21 (b), T4.25, A7.9, A14.8. Problem A14.8 requires the file

`spacecraft_landing_data.m`.Homework 5 (due 2/16). Exercise A3.21 (a,b), three additional problems, and exercise A3.11.

Homework 6 (due 2/23). Exercise A12.6, A4.4, T4.43 (b,c), T5.19, T5.21 (a,b,c), A4.30.

Homework is due at 4PM on the due date. It can be submitted at the start of the lecture or in the EE236B homework box in the TA meeting room (67-112 Engineering 4).

Homework solutions and grades will be posted on the EE Department EEweb course website. (Follow the links to “Assignments” or “Grades”.)

**Lectures**: Kinsey 1200B, Tuesday & Thursday 16:00-17:50PM.

**Discussion**: Boelter 3400, Friday 15:00-15:50PM.

**Office hours**

Prof. Vandenberghe: Wednesday 13:00-16:00, Rm 66-147L Eng. 4.

Xin Jiang: Thursday 11:00-12:00, Rm 67-112 Eng. 4.

Hemant Saggar: Monday 11:00-12:00, Rm 67-112 Eng. 4.

**Textbook**
The textbook is *Convex
Optimization*, available online and in hard copy at the UCLA bookstore.
The following books are useful as 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, March 22, 11:30AM-14:30 PM.
The weights in the final grade are: homework 20%, final exam 80%.

**Software**.
We will use CVX,
a MATLAB software package for convex optimization.
Python users are welcome to use CVXPY
instead of MATLAB and CVX.
Julia users are welcome to use Convex.jl.