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Sanjeev Arora, Princeton University. In recent years Princeton has moved all course pages to Canvas, which is only accessible via campus loging. I have placed course material for my main courses online: COS324: Introduction to Machine Learning, and COS 514: Fundamentals of Deep Learning. Some old course pages:
Sanjeev Arora Princeton University, Princeton, New Jersey and Institute for Advanced Study, Princeton, New Jersey July 2020 ICML'20: Proceedings of the 37th International Conference on Machine Learning
Computing a nonnegative matrix factorization--provably. S Arora, R Ge, R Kannan, A Moitra. Proceedings of the forty-fourth annual ACM symposium on Theory of computing …. , 2012. 498. 2012. 文章 1–20. 展开. Professor of Computer Science, Princeton University - 引用次数：36,318 次 - theoretical machine learning ...
Sanjeev Arora is the Charles C. Fitzmorris Professor in Computer Science. He joined Princeton in 1994 after earning his doctorate from the University of California, Berkeley. He was a visiting professor at the Weizmann Institute in 2007, a visiting researcher at Microsoft in 2006-07, and a visiting associate professor at Berkeley during 2001-02.
Sanjeev Arora is Charles C. Fitzmorris Professor of Computer Science at Princeton University. He got his PhD at UC Berkeley in 1994. His research area spans several areas of theoretical Computer Science, including computational complexity and algorithm design, and theoretical problems in machine learning.
20 de abr. de 2009 · Something on Semantic Scholar broke unexpectedly. Our team has been notified and will look into it, in the meantime please try refreshing the page. If you need more help, reach out to us at feedback@semanticscholar.org. Semantic Scholar profile for Sanjeev Arora, with 682 highly influential citations and 77 scientific research papers.
Sanjeev Arora and Boaz Barak. Cambridge University Press. This is a textbook on computational complexity theory. It is intended as a text for an advanced undergraduate course or introductory graduate course, or as a reference for researchers and students in computer science and allied fields such as mathematics and physics.
