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Winter 2022
Jul 02, 2022
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Sections Found
Theory of Machine Learning. - 6525 - MATH 562 - 001
Concentration inequalities, PAC model, VC dimension, Rademacher complexity, convex optimization, gradient descent, boosting, kernels, support vector machines, regression and learning bounds. Further topics selected from: Gaussian processes, online learning, regret bounds, basic neural network theory.

Prerequisites: MATH 462 or COMP 451 or (COMP 551, MATH 222, MATH 223 and MATH 324) or ECSE 551.
Restrictions: Not open to students who have taken or are taking COMP 562. Not open to students who have taken COMP 599 when the topic was "Statistical Learning Theory" or "Mathematical Topics for Machine Learning". Not open to students who have taken COMP 598 when the topic was"Mathematical Foundations of Machine Learning".

Associated Term: Winter 2022
Registration Dates: Jun 01, 2021 to Jan 18, 2022

Lecture Schedule Type
4.000 Credits
View Catalog Entry

Scheduled Meeting Times
Time Days Where Date Range Schedule Type Instructors
11:35 am - 12:55 pm TR Stewart Biology Building N2/2 Jan 05, 2022 - Apr 12, 2022 Lecture Adam M. Oberman



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