"The Best of Many Worlds: Dual Mirror Descent for Online Allocation Problems."

Balseiro, Santiago R., Haihao Lu, and Vahab Mirrokni. Operations Research Vol. 71, No. 1 (2023): 101-119.

"An O(sr)-Resolution ODE Framework for Discrete-time Optimization Algorithms and Applications to the Linear Convergence of Minimax Problems."

Lu, Haihao. Mathematical Programming Vol. 194, No. 1-2 (2022): 1061-1112.

"Limiting Behaviors of Nonconvex-nonconcave Minimax Optimization via Continuous-time Systems."

Benjamin Grimmer, Haihao Lu, Pratik Worah, and Vahab Mirrokni. In Proceedings of The 33rd International Conference on Algorithmic Learning Theory, Paris, France: March 2022.

"Frank-Wolfe Methods with an Unbounded Feasible Region and Applications to Structured Learning."

Wang, Haoyue, Haihao Lu, and Rahul Mazumder. SIAM Journal on Optimization Vol. 32, No. 4 (2022): 2938-2968.

"Practical Large-Scale Linear Programming using Primal-dual Hybrid Gradient."

David Applegate, Mateo Diaz, Oliver Hinder, Haihao Lu, Miles Lubin, Brendan O'Donoghue, and Warren Schudy. In Proceedings of the 35th Conference on Neural Information Processing Systems, December 2021.

"Regularized Online Allocation Problems: Fairness and Beyond."

Santiago Balseiro, Haihao Lu, and Vahab Mirrokni. In Proceedings of the 38th International Conference on Machine Learning, July 2021.