Convex Optimization

This is a webpage for 2010 course at the Weizmann Institute.

Mondays and Wednesdays 10:00-12:00, February 22nd through March 10th, 10:00-12:00, Ziskind 1
Mondays 9:00-11:00 at Ziskind 286, Wednesdays 9:00-11:00 at Ziskind 1, March 15th through 24th
Final exam: April 14th 10am

Lecturer: Nati Srebro, TTI-Chicago.

Course Description

The course will cover techniques in unconstrained and constrained convex optimization and a practical introduction to convex duality. The course will focus on (1) formulating and understanding convex optimization problems and studying their properties; (2) presenting and understanding optimization approaches; and (3) understanding the dual problem. Limited theoretical analysis of convergence properties of methods will be presented. Examples will be mostly from data fitting and machine learning.

Specific Topics:

Text Books

The required textbook for the class is: The book is available online here. About 80% of the material covered in the class can be found in the above book.

Supplemental recommended books:

In particular, additional material on unconstrained optimization techniques, not covered by Boyd and Vandenberghe, can be found in the first two of the above three books.

Requirements and Grading:

There will be three homework assignments, counting toward 40% of the grade (13% each). Assignments must be typed (not handwritten) and submitted electronically in PDF.

The remaining 60% of the grade will be based on a final exam.

Students will also be expected to read reading assignments from Boyd and Vandenberghe supplementing and providing background to topics discussed in class. The material from these reading assignments will be covered by the problem sets and in the exam, and will be assumed in lectures.

Lectures and Required Reading:

Monday, February 22nd
Wednesday, February 24nd

Assignment 1 out.
Monday, March 1st
Optional enrichment problem set 1 ½ available.
Wednesday, March 3rd
Monday, March 8th
Wednesday, March 10th

Assignment 2 Out
Reading before lecture: Sections 3.3, 2.4.1, 2.6.1, 2.6.2
Monday, March 15th
Assignment 1 Due
Assignment 2 Out
Wednesday, March 17th
Monday, March 22nd
Wednesday, March 24th
Assignment 3 Out


Assignment 1: Convexity and Unconstrained Optimization (Note corrected definition of Strong Convexity in Problem 3; "½" instead of "2" in Problem 6(a); and additional hint in Problem 4(c))
Optional Enrichment Assignment 1: Conjugate Gradient Descent and Quasi-Newton Methods.
Assignment 2: Duality (Updated March 24th: correction to 1(b))
Assignment 3: Constrained Optimization

Last modified: Wed Mar 24 16:40:05 Jerusalem Standard Time 2010