diff --git a/README.md b/README.md index 2a5f65d..46e6483 100644 --- a/README.md +++ b/README.md @@ -645,8 +645,7 @@ Topics covered include probability theory and Bayesian inference; univariate dis - Regression will be covered if time permits. - [Assignments](http://www.cs.cornell.edu/courses/CS4786/2015sp/assignments.htm) - [Lectures](http://www.cs.cornell.edu/courses/CS4786/2015sp/lectures.htm) -- [CVX 101](https://class.stanford.edu/courses/Engineering/CVX101/Winter2014/info) **Convex Optimization** *Stanford University* Assignments Lecture Notes - Readings +- [CVX 101](https://class.stanford.edu/courses/Engineering/CVX101/Winter2014/info) **Convex Optimization** *Stanford University* Assignments Lecture Notes Readings - The course concentrates on recognizing and solving convex optimization problems that arise in applications. Topics addressed include the following. Convex sets, functions, and optimization problems. Basics of convex analysis. Least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems. Optimality conditions, duality theory, theorems of alternative, and applications. Interior-point methods. Applications to signal processing, statistics and machine learning, control and mechanical engineering, digital and analog circuit design, and finance. - [Textbook](http://web.stanford.edu/~boyd/cvxbook/) - [Lectures and Assignments](https://class.stanford.edu/courses/Engineering/CVX101/Winter2014/courseware/7206c57866504e83821d00b5d3f80793/)