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.

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

Three Recent Papers

"Generalized Stochastic Frank-Wolfe Algorithm with Stochastic “Substitute” Gradient for Structured Convex Optimization." Lu, Haihao, and Robert M. Freund, submitted

"Accelerating Greedy Coordinate Descent Methods."  Lu, Haihao, Robert M. Freund, and Vahab Mirrokni, to appear at International Conference on Machine Learning (ICML) 2018, Stockholm.

"Relatively-Smooth Convex Optimization by First-Order Methods, and Applications," Lu, Haihao, Robert M. Freund, and Yurii Nesterov, SIAM Journal on Optimization (2018), vol. 28 (1), pp. 333-354.

 

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