CMPS290O: Algorithmic Foundations of Convex Optimization

*****COURSES ARE SUBJECT TO CHANGE*****

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

YearFallWinterSpringSummer
2018-19

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