ORIE 5320

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  • Schedule of Classes - January 5, 2026 3:59PM EST

ORIE 5320
Optimization for AI

Course information provided by the 2025-2026 Catalog.

From fitting regression models to training neural networks, many problems in artificial intelligence can be cast as optimization problems. This course studies the fundamentals of optimization as they apply to artificial intelligence. Much of the focus will be on convex optimization, covering topics such as convex analysis, gradient descent for constrained and unconstrained problems, proximal gradient descent, variants of Newton’s method, and the Frank-Wolfe algorithm. The treatment will be at a fairly sophisticated level, giving sound justifications for the algorithms studied.


Enrollment Priority Recommended prerequisite: integral calculus at the level of Math 1910 and linear algebra at the level of Math 2940.

Last 1 Terms Offered (None)

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Syllabi: none

  •   Regular Academic Session.  Choose one lecture and one laboratory. Combined with: ORIE 3320

  • 4 Credits Stdnt Opt

  • 13704 ORIE 5320   LEC 001

  •  

  • Instruction Mode: In Person

    Enrollment limited to: graduate students.

  • 13705 ORIE 5320   LAB 401

  •  

  • Instruction Mode: In Person

  • 13706 ORIE 5320   LAB 402

  •  

  • Instruction Mode: In Person

Syllabi: none

  •   Regular Academic Session. 

  • 3 Credits Graded

  • 18108 ORIE 5320   LEC 030

  •  

  • Instruction Mode: In Person

    Enrollment limited to: Cornell Tech students.