Course Description 

Optimization has long been playing an important, indispensable role in statistics and machine learning. This has become even more so in recent years, since the current era of big data presents many theoretical and computational challenges to the statistics and machine learning communities. This course aims at introducing a series of core topics lying at the intersection of modern optimization and statistics. We will particularly focus on the interplay between sample and computational complexity.  

Prerequisites 

The prerequisites to this course are undergraduate linear algebra, calculus, real analysis, probability theory and convex optimization.