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NOTE: Course information changes frequently, including Methods of Instruction. Please revisit these pages periodically for the most recent and up-to-date course information.


Fall 2022 Industrial Engineering and Operations Research E6617 section 001
Machine Learning and High-Dimensional Da
Mchn lrning&Hgh-dmntnl da

Call Number 11693
Day & Time
Location
M 7:10pm-9:40pm
545 Seeley W. Mudd Building
Points 3
Grading Mode Standard
Approvals Required None
Instructor Krzysztof M Choromanski
Type LECTURE
Method of Instruction In-Person
Course Description Discusses recent advances in fields of machine learning: kernel methods, neural networks (various generative adversarial net architectures), and reinforcement learning (with applications in robotics). Quasi Monte Carlo methods in the context of approximating RBF kernels via orthogonal transforms (instances of the structured technique). Will discuss techniques such as TD(0), TD(λ), LSTDQ, LSPI, DQN.
Web Site Vergil
Department Industrial Engineering and Operations Research
Enrollment 18 students (40 max) as of 5:52PM Tuesday, December 6, 2022
Subject Industrial Engineering and Operations Research
Number E6617
Section 001
Division School of Engineering and Applied Science: Graduate
Campus Morningside
Section key 20223IEOR6617E001

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SIS update 12/06/22 17:52    web update 12/06/22 21:13