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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 8:08PM Friday, March 31, 2023 |
| 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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