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TITLE: From Data to Decisions : A Robust Optimization Perspective"
ABSTRACT:
We discuss prescribing optimal decisions in a framework where their cost depends on uncertain problem parameters that need to be learned from historical data. We claim that robust optimization methods have an enormous untapped potential when decisions based on limited data. We indeed identify a class of robust optimization formulations which possess statistical optimality guarantees among all functions mapping data to decisions.
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.
