Robert M. Freund

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Robert M. Freund

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Robert Freund is the Theresa Seley Professor in Management Science and a Professor of Operations Research at the MIT Sloan School of Management.  

His main research interests are in convex optimization, computational complexity and related computational science, convex geometry, large-scale nonlinear optimization, and related mathematical systems.  His more recent work is in first-order methods and their connections to statistical and machine learning. He has served as coeditor of the journal Mathematical Programming and associate editor of several optimization and operations research journals. He is the former CoDirector of MIT Operations Research Center, the MIT Program in Computation for Design and Optimization, and the former Chair of the INFORMS Optimization Section. He also served a term as Deputy Dean of the Sloan School at MIT (2008-11).

Freund received the Longuet-Higgins Prize in computer vision (2007) as well as numerous teaching and education awards at MIT in conjunction with the course and textbook (coauthored with Dimitris Bertsimas) Data, Models, and Decisions:  the Fundamentals of Management Science.

Freund holds a BA in mathematics from Princeton University and an MS and a PhD in operations research from Stanford University. 

Honors

Freund elected as an INFORMS Fellow

Freund wins MIT’s 2020 Seegal prize

Publications

"An Oblivious Ellipsoid Algorithm for Solving a System of (In)Feasible Linear Inequalities."

Lamperski, Jourdain, Robert M. Freund, and Michael J. Todd. Mathematics of Operations Research. Forthcoming.

"Nonlinear Conjugate Gradient Methods: Worst-case Convergence Rates via Computer-assisted Analyses."

Shuvomoy Das Gupta, Robert M. Freund, Xu Andy Sun, Adrien Taylor, Working Paper. January 2023.

"Using Taylor-approximated Gradients to Improve the Frank-Wolfe Method for Empirical Risk Minimization."

Xiong, Zikai and Robert M. Freund, MIT Sloan Working Paper 6791-22. Cambridge, MA: MIT Sloan School of Management, 2022. Additional Results and Extensions.

"Generalized Stochastic Frank-Wolfe Algorithm with Stochastic 'Substitute' Gradient for Structured Convex Optimization."

Lu, Haihao, and Robert M. Freund. Mathematical Programming Vol. 187, No. 1-2 (2021): 317-349. Working Paper.

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