Homework solutions and grades are posted on the EEweb course website. (Follow the links to “Assignments” or “Grades”.)
Homework 1 (due 1/14). Exercises 2.5, 2.12 (b,d,e,g), 2.28 in the textbook, plus an additional problem. The last problem requires the Matlab file illumdata.m and the CVX software package.
Homework 2 (due 1/21). Exercises 3.2, 3.19 (a), 3.21 (b), and some additional problems. The last problem requires the Matlab files spline_data.m and bsplines.m.
Homework 3 (due 1/28). Exercises 3.23 (a), 3.26 (b), 3.54, 4.8 (e), and some additional problems.
Homework 4 (due 2/4). Exercises 4.21 (b), 4.25, 4.26 (b), and some additional problems.
Homework 5 (due 2/11). Exercises 4.43 (b,c), 5.6, 5.11, 5.21, and two additional problems.
Lectures: Geology 4660. Tuesday & Thursday 10:00-11:50AM.
Textbook The textbook is Convex Optimization, available online and in hard copy at the UCLA bookstore. Some books that can serve as secondary (and entirely optional) reference texts are:
A. Ben-Tal and A. Nemirovski, Lectures on Modern Convex Optimization, Society for Industrial and Applied Mathematics.
D. Bertsekas, A. Nedic, A.E. Ozdaglar, Convex Analysis and Optimization, Athena Scientific.
D. Bertsekas, Convex Optimization Theory, Athena Scientific.
Y. Nesterov, Introductory Lectures on Convex Optimization: A Basic Course, Kluwer.
D. Bertsekas, Nonlinear Programming, Athena Scientific.
D. Luenberger, Linear and Nonlinear Programming, Addison-Wesley.
J. Nocedal and S. Wright, Numerical Optimization, Springer.
Course requirements. Weekly homework assignments; open-book final exam on Monday, March 15, 11:30-2:30PM. The approximate weights in the final grade are: homework 20%, final exam 80%.
Software. We will use CVX, a Matlab software package for convex optimization.