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
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.