Optimization for Machine Learning

Event Sponsor: 
Mathmatics and Computer Science Division Seminar - LANS
Start Date: 
Nov 28 2018 - 10:30am
Building 240/Room 4301
Argonne National Laboratory
Sven Leyffer
Speaker(s) Title: 
Argonne National Laboratory, MCS

We review optimization methods that underpin machine-learning approaches. Our goal is to provide an overview of the connections between optimization and machine learning. We discuss the impact of nonsmooth optimization methods, splitting methods, gradient and Newton-type methods. We also examine the impact of different model formulations such as robust optimization, mixed-integer optimization, and complementarity constraints. Our goal is to highlight both the limitations and promises of optimization methodologies and formulations.

Miscellaneous Information: 

This seminar will be streamed. See details at https://anlpress.cels.anl.gov/cels-seminars/.

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Upcoming Seminars
October 24, 2018, "Theory for BART" Veronika Rockova, Assistant Professor of Econometrics and Statistics, University of Chicago Booth School of Business
October 31, 2018, "Sandeep Madireddy MCS seminar, see www.anl.gov/events"
November 7, 2018, "Ahmed Attia MCS seminar, see www.anl.gov/events"
November 13, 2018, "Quantifying the uncertainty in cardiovascular digital twins through model reduction, Bayesian inference and propagation using model ensembles." Daniele Schiavazzi, Assistant Professor, Department of Applied and Computational Mathematics and Statistics, Notre Dame
November 28, 2018, "Optimization for Machine Learning" Sven Leyffer, Senior Computational Mathematician, MCS/ANL
December 12, 2018, "TBA" Michael Servis, Postdoctoral Researcher, Washington State University