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1 - 1 of 1 results for: CS 329M: Topics in Artificial Intelligence: Algorithms of Advanced Machine Learning

CS 329M: Topics in Artificial Intelligence: Algorithms of Advanced Machine Learning

This advanced graduate course explores in depth several important classes of algorithms in modern machine learning. We will focus on understanding the mathematical properties of these algorithms in order to gain deeper insights on when and why they perform well. We will also study applications of each algorithm on interesting, real-world settings. Topics include: spectral clustering, tensor decomposition, Hamiltonian Monte Carlo, adversarial training, and variational approximation. Students will learn mathematical techniques for analyzing these algorithms and hands-on experience in using them. We will supplement the lectures with latest papers and there will be a significant research project component to the class. Prerequisites: Probability ( CS 109), linear algebra ( Math 113), machine learning ( CS 229), and some coding experience.
Terms: Spr | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: Zou, J. (PI)
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