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YINS Seminar Archives: Suvrit Sra (Nov. 20, 2019)
YINS Seminar Archives: Suvrit Sra (Nov. 20, 2019)
“ReLU nets are powerful memorizers: a tight analysis of finite sample expressive power”
Speaker: Suvrit Sra, Associate Professor, Department of Electrical Engineering & Computer Science, Institute for Data, Systems & Society (IDSS), Massachusetts Institute of Technology
Suvrit Sra is an Associate Professor in the EECS Department at MIT, and also a core faculty member of the Laboratory for Information and Decision Systems (LIDS), the Institute for Data, Systems, and Society (IDSS), as well as a member of MIT-ML and Statistics groups. He obtained his PhD in Computer Science from the University of Texas at Austin. Before moving to MIT, he was a Senior Research Scientist at the Max Planck Institute for Intelligent Systems, Tübingen, Germany. He has held visiting faculty positions at UC Berkeley (EECS) and Carnegie Mellon University (Machine Learning Department) during 2013-2014. His research bridges a number of mathematical areas such as differential geometry, matrix analysis, convex analysis, probability theory, and optimization with machine learning. He founded the OPT (Optimization for Machine Learning) series of workshops, held from OPT2008–2017 at the NeurIPS (erstwhile NIPS) conference. He has co-edited a book with the same name (MIT Press, 2011). He is also a co-founder and chief scientist of a healthcare-AI startup.