"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.

"Relatively Smooth Convex Optimization by First-Order Methods, and Applications."

Lu, Haihao, Robert M. Freund, and Yurii Nesterov. SIAM Journal on Optimization Vol. 28, No. 1 (2018): 333-354.

"Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods."

Freund, Robert M., Paul Grigas, and Rahul Mazumder (submitted), MIT Sloan Working Paper 5536-18. Cambridge, MA: MIT Sloan School of Management, 2018.

"A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives."

Freund, Robert M., Paul Grigas, and Rahul Mazumder. Annals of Statistics Vol. 45, No. 6 (2017): 2328-2364.

"An Extended Frank-Wolfe Method with 'In-Face' Directions, and its Application to Low-Rank Matrix Completion."

Freund, Robert M., Paul Grigas, and Rahul Mazumder. SIAM Journal on Optimization Vol. 27, No. 1 (2017): 319-346.

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