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   Leastsquares 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   Secondorder 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

