"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.

"Analysis of the Frank-Wolfe Method for Convex Composite Optimization involving a Logarithmically-Homogeneous Barrier."

Zhao, Renbo, and Robert M. Freund, MIT Sloan Working Paper 6210-20. Cambridge, MA: MIT Sloan School of Management, October 2020.

"Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization."

Geoffrey Negiar, Gideon Dresdner, Alicia Yi-Ting Tsai, Laurent El Ghaoui, Francesco Locatello, Robert M. Freund, and Fabian Pedregosa. In Proceedings of the Thirty-seventh International Conference on Machine Learning (ICML) 2020, edited by Alexandre Bouchard-Côté and Samory Kpotufe. San Diego, CA: July 2020.

"Accelerated Residual Methods for the Iterative Solution of Systems of Equations."

Nguyen, Ngoc Cuong, Pablo Fernandez, Robert M. Freund, and Jaime Peraire. SIAM Journal of Scientific Computing Vol. 40, No. 5 (2018): A3157-79. Working Paper.

"New Computational Guarantees for Solving Convex Optimization Problems with First Order Methods, via a Function Growth Condition Measure."

Freund, Robert M., and Haihao Lu. Mathematical Programming Vol. 170, No. 2 (2018): 445-477.

"Accelerating Greedy Coordinate Descent Methods."

Haihao Lu, Robert M. Freund, and Vahab Morrokni. In 35th International Conference on Machine Learning (ICML) 2018, edited by Iain Murray and Shakir Mohamed. Stockholm, Sweden: July 2018. Supplementary Material.

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