基本信息
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Bio
Professor Anandkumar's research interests are in the areas of large-scale machine learning, non-convex optimization and high-dimensional statistics. In particular, she has been spearheading the development and analysis of tensor algorithms for machine learning. Tensor decomposition methods are embarrassingly parallel and scalable to enormous datasets. They are guaranteed to converge to the global optimum and yield consistent estimates for many probabilistic models such as topic models, community models, and hidden Markov models. More generally, Professor Anandkumar has been investigating efficient techniques to speed up non-convex optimization such as escaping saddle points efficiently.
Research Interests
Papers共 477 篇Author StatisticsCo-AuthorSimilar Experts
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ICML 2024 (2024)
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CoRRno. 2 (2024): 195-208
Shengchao Liu,Weitao Du, Yanjing Li,Zhuoxinran Li,Vignesh Bhethanabotla, Nakul Rampal, Omar Yaghi,Christian Borgs,Anima Anandkumar,Hongyu Guo,Jennifer Chayes
CoRR (2024)
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CoRR (2024)
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Runzhuo Ma,Dani Kiyasseh,Jasper A. Laca,Rafal Kocielnik,Elyssa Y. Wong,Timothy N. Chu,Steven Cen, Cherine H. Yang, Istabraq S. Dalieh,Taseen F. Haque, Mitch G. Goldenberg, Xiuzhen Huang,
Md Ashiqur Rahman, Robert Joseph George, Mogab Elleithy, Daniel Leibovici,Zongyi Li,Boris Bonev,Colin White,Julius Berner,Raymond A. Yeh,Jean Kossaifi,Kamyar Azizzadenesheli,Anima Anandkumar
CoRR (2024)
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Vignesh Gopakumar,Stanislas Pamela,Lorenzo Zanisi,Zongyi Li, Ander Gray, Daniel Brennand, Nitesh Bhatia, Gregory Stathopoulos,Matt Kusner, Marc Peter Deisenroth,Anima Anandkumar
NUCLEAR FUSIONno. 5 (2024)
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