CSE280O: Algorithmic Foundations of Convex Optimization

Focuses on some of the foundational aspects of convex and its relationship to modern machine learning. Discusses positive results--how can you solve convex optimization problems--and negative ones with statements like This family of problems is too hard to be solved in reasonable time. Course is divided into three parts, each exploring a different aspect of convex optimization: 1) algorithmic frameworks; 2) Oracle complexities; 3) the power of randomness. Through this course students are exposed to general concepts of convex geometry, learning theory, and rigorous proofs. (formerly CMPS 290O.)

 

Prerequisite(s): CSE 201 and CSE 242. Enrollment is restricted to computer engineering and computer science graduate students.

5 credits

Year Fall Winter Spring Summer
2025-26
  • Section 01
    Lindsey A Kuper (lkuper)
    Tyler R Sorensen (tysorens)
  • Section 01
    Lindsey A Kuper (lkuper)
    Tyler R Sorensen (tysorens)
  • Section 01
    Lindsey A Kuper (lkuper)
    Tyler R Sorensen (tysorens)
2024-25
  • Section 01
    Lindsey Kuper (lkuper)
    Tyler Rey Sorensen (tysorens)
  • Section 01
    Lindsey Kuper (lkuper)
    Tyler Rey Sorensen (tysorens)
  • Section 01
    Lindsey Kuper (lkuper)
    Tyler Rey Sorensen (tysorens)
2023-24
  • Section 01
    Lindsey Kuper (lkuper)
    Tyler Rey Sorensen (tysorens)
  • Section 01
    Lindsey Kuper (lkuper)
    Tyler Rey Sorensen (tysorens)
  • Section 01
    Lindsey Kuper (lkuper)
    Tyler Rey Sorensen (tysorens)
2022-23
  • Section 01
    Lindsey Kuper (lkuper)
    Tyler Rey Sorensen (tysorens)
Comments

Formerly CMPS 280O

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