[Lisa_seminaires] [Tea Talk] Bart Van Parys (MIT) Fri Jan 26 1:30PM AA1360

Michael Noukhovitch mnoukhov at gmail.com
Lun 22 Jan 15:35:33 EST 2018


Hi all!

We will have a researcher from MIT, *Bart Van Parys*, giving a talk on *Friday
Jan 26th at 1:30PM* in room *AA1360*.

Note the later time, *1:30!*

This is a seminar is organized in collaboration with the Canada Research
Chair in Decision Making under Uncertainty at GERAD! So this is ideal for
all the optimization fans out there!

Based on my experience, this will be a great talk and coming to it should
be an easy decision!
Michael

*KEYWORDS *Optimization, Sparse Regression, Generalization

*TITLE *Modern Optimization for Sparse Learning and Robust Analytics

*ABSTRACT*
We discuss the tremendous potential of integer optimization
methods for learning predictive models from high-dimensional data via
exact sparse regression. We show that novel integer formulations can
solve exact sparse regression problems of sizes counting p=100,000s
covariates for n=10,000s of samples. That is, two orders of magnitude
more than current state of the art methods. We also indicate that robust
optimization methods can help practitioners make data-driven decisions
which are safeguarded against over-calibration to one particular data
set. We claim that robust optimization methods have an enormous untapped
potential when making subsequent decisions based on data.

*BIO*
Bart Van Parys is currently a postdoctoral researcher working
with Prof. Dimitris Bertsimas at the MIT Sloan School of Management. His
research interests are situated on the interface between optimization
and machine learning. In 2015 he obtained his Ph.D. in control theory at
the Swiss Federal Institute of Technology (ETH) in Zurich under the
supervision of Prof. Manfred Morari. He received his M.E. from the
University of Leuven in 2011.
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