Wednesday, February 10, 2021 - 11:00am to Thursday, February 11, 2021 - 11:55am
Event Calendar Category
Other LIDS Events
Speaker Name
Nati Srebro
Affiliation
Toyota Technological Institute at Chicago
Abstract
Biography
Nati (Nathan) Srebro is a professor at the Toyota Technological Institute at Chicago, with cross-appointments at the University of Chicago Dept. of Computer Science and Committee on Computational and Applied Mathematics. He obtained his Ph.D. at the Massachusetts Institute of Technology (MIT) in 2004 and previously was a post-doctoral fellow at the University of Toronto, a Visiting Scientist at IBM, and an Associate Professor at the Technion. Prof. Srebro’s research encompasses methodological, statistical, and computational aspects of Machine Learning, as well as related problems in Optimization. Some of Prof. Srebro’s significant contributions include work on learning “wider” Markov networks; introducing the use of the nuclear norm for machine learning and matrix reconstruction; work on fast optimization techniques for machine learning, the optimality of stochastic methods, and on the relationship between learning and optimization more broadly. His current interests include understanding deep learning through a detailed understanding of optimization; distributed and federated learning; algorithmic fairness and practical adaptive data analysis. Prof. Srebro is currently on sabbatical visiting EPFL in Lausanne.