"Large-scale Optimization Methods for Data-science Applications."

Lu, Haihao. PhD diss., Massachusetts Institute of Technology, Department of Mathematics, 2019.

"'Relative Continuity' for Non-Lipschitz Nonsmooth Convex Optimization Using Stochastic (or Deterministic) Mirror Descent."

Lu, Haihao. INFORMS Journal on Optimization Vol. 1, No. 4 (2019): 288-303.

"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. 1-2 (2018): 445-477.

"Accelerating Greedy Coordinate Descent Methods."

Haihao Lu, Robert M. Freund, and Vahab Mirrokni. In Proceedings of the 35th International Conference on Machine Learning, Stockholm, Sweden: July 2018.

"Approximate Leave-one-out for Fast Parameter Tuning in High Dimensions."

Shuaiwen Wang, Wenda Zhou, Haihao Lu, Arian Maleki, and Vahab Mirrokni. In Proceedings of the 35th International Conference on Machine Learning, Stockholm, Sweden: July 2018.

"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. Working Paper.