Invited talk | Anima Anandkumar
Anima Anandkumar
2023 Invited talk
in
Workshop: Generative AI and Biology (GenBio@NeurIPS2023)
in
Workshop: Generative AI and Biology (GenBio@NeurIPS2023)
Abstract
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.
Speaker
Anima Anandkumar
Anima Anandkumar is a Bren professor at Caltech. Her research spans both theoretical and practical aspects of large-scale machine learning. In particular, she has spearheaded research in neural operators, tensor-algebraic methods, non-convex optimization, probabilistic models and deep learning.
Anima is the recipient of several awards and honors such as the Bren named chair professorship at Caltech, Alfred. P. Sloan Fellowship, Young investigator awards from the Air Force and Army research offices, Faculty fellowships from Microsoft, Google and Adobe, and several best paper awards.
Anima received her B.Tech in Electrical Engineering from IIT Madras in 2004 and her PhD from Cornell University in 2009. She was a postdoctoral researcher at MIT from 2009 to 2010, a visiting researcher at Microsoft Research New England in 2012 and 2014, an assistant professor at U.C. Irvine between 2010 and 2016, an associate professor at U.C. Irvine between 2016 and 2017 and a principal scientist at Amazon Web Services between 2016 and 2018.
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