CSE290O: Algorithmic Foundations of Convex Optimization

This course will focus on some of the foundational aspects of convex optimization and its relationship to modern machine learning. The course will discuss both positive results: how can you solve convex optimization problems; but also negative ones with statements like: ‘this family of problems is too hard to be solved in reasonable time’. The course will be divided into three parts, each one explores a different aspect of convex optimization: i) Algorithmic frameworks ii) Oracle complexities, and iii) Power of randomness. Through this course students will be exposed to general concepts of convex geometry, learning theory, and rigorous proofs.

5 credits

Year	Fall	Winter	Spring	Summer

Comments

Formerly CMPS 290O

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