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Bart P.G. Van Parys
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Bart Van Parys is an Assistant Professor in Operations Research and Statistics at the MIT Sloan School of Management.
His research interests are located on the interface between robust optimization and machine learning. He has completed a postdoctoral position at MIT Sloan in the Operations Research and Statistics Group.
Bart holds a BS in electrical engineering and an MS in engineering mathematics from KU Leuven. He received his PhD in control theory at ETH Zurich under the supervision of Prof. Manfred Morari.
Publications🔗
"From Data to Decisions: Distributionally Robust Optimization is Optimal."
Van Parys, Bart P.G., Peyman Mohajerin Esfahani, and Daniel Kuhn. Management Science. Forthcoming. arXiv Preprint.
"Sparse High-Dimensional Regression: Exact Scalable Algorithms and Phase Transitions."
Bertsimas, Dimitris, and Bart P.G. Van Parys. Annals of Statistics. Forthcoming. arXiv Preprint.
"Sparse Regression: Scalable Algorithms and Empirical Performance."
Bertsimas, Dimitris, Jean Pauphilet, and Bart P.G. Van Parys. Statistical Science. Forthcoming.
"Sparse Hierarchical Regression with Polynomials."
Bertsimas, Dimitris and Bart P. G. Van Parys. Machine Learning Vol. 109, (2020): 973-997.
"Distributionally Robust Expectation Inequalities for Structured Distributions."
Van Parys, Bart P. G., Paul J. Goulart, and Manfred Morari. Mathematical Programming Vol. 173, No. 1-2 (2019): 251-280. Download Paper.
"Multivariate Chebyshev Inequality With Estimated Mean and Variance."
Stellato, Bartolomeo, Bart P. G. Van Parys, and Paul J. Goulart. The American Statistician Vol. 71, No. 2 (2017): 123-127. Download Paper.