Lectures

We follow closely the textbook Optimization Models. You can also find the livebook useful.

Week Lecture Date Part Lecture
1 1 1/20/15 Linear algebra Introduction
1 2 1/22/15 Vectors and functions
2 3 1/27/15 Matrices and linear maps
2 4 1/29/15 Symmetric matrices and their eigenvalues
3 5 2/3/15 Singular value decomposition
3 6 2/5/15 Linear equations
4 7 2/10/15 Least-squares and variants
4 8 2/12/15 Applications and limitations of linear algebra
5 9 2/17/15 Review
5 2/19/15 Quiz
6 10 2/24/15 Convex optimization Convexity
6 11 2/26/15 Convex optimization problems
7 12 3/3/15 Subgradients and subgradient methods
7 13 3/5/15 Duality
8 14 3/10/15 Applications of duality
8 3/12/15 MIDTERM
9 16 3/17/15 Conic optimization Linear optimization
9 17 3/19/15 Convex quadratic optimization
10 18 3/31/15 Second-order cone optimization
10 19 4/2/15 Robust optimization
11 20 4/7/15 Semidefinite programming
11 21 4/9/15 Geometric programming
12 4/14/15 Quiz
12 22 4/16/15 Applications Machine learning applications
13 23 4/21/15 Control applications
13 24 4/23/15 Finance applications
14 25 4/28/15 Engineering design applications
14 26 4/30/15 Review
TBD Final