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Robert Freund is the Theresa Seley Professor in Management Science at the MIT Sloan School of Management. He conducts research in large-scale optimization – both applied and theoretical – as well as related mathematical systems. Freund teaches MBA courses in business analytics and quantitative methods, as well as advanced courses in  optimization theory. Freund is the co-author, along with Dimitris Bertsimas, of the MBA textbook Data, Models, and Decisions: the Fundamentals of Management Science. Bio and CV can be found here.

(You may also be looking for my name-fellow and colleague, Daniel Freund. His website can be found here.)

Publications/Talks/Collaborators
Robert Freund, Professor in Management Science

Three Recent Papers

"Analysis of the Frank-Wolfe Method for Logarithmically-Homogeneous Barriers, with an Extension", with Renbo Zhao, submitted.

"Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization," with Geoffrey Négiar, Gideon Dresdner, Alicia Yi-Ting Tsai, Laurent El Ghaoui, Francesco Locatello, and Fabian Pedregosa, to appear at International Conference on Machine Learning (ICML) 2020.

"An 'Oblivious' Ellipsoid Algorithm for Solving a System of (In)Feasible Linear Inequalities," with Jourdain Lamperski and Michael Todd, conditionally accepted to Mathematics of Operations Research.

Research Interests

  • Nonlinear optimization theory, applications, and computation -- current focus on algorithmic theory and practice of first-order methods
  • Computational complexity of nonlinear optimization
  • Interior-point methods in convex optimization
  • Computational science
  • Related mathematical systems
  • Applied optimization in management and engineering
  • Linear optimization
  • Fixed-point methods