"On a Unified and Simplified Proof for the Ergodic Convergence Rates of PPM, PDHG and ADMM."

Lu, Haihao and Jinwen Yang, MIT Sloan Working Paper 7106-23. Cambridge, MA: MIT Sloan School of Management, May 2023. arXiv Preprint.

"On the Infimal Sub-differential Size of Primal-dual Hybrid Gradient Method and Beyond."

Lu, Haihao and Jinwen Yang, MIT Sloan Working Paper 7108-22. Cambridge, MA: MIT Sloan School of Management, March 2023. arXiv Preprint.

"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."

Grimmer, Benjamin, Haihao Lu, Pratik Worah, and Vahab Mirrokni. Proceedings of The 33rd International Conference on Algorithmic Learning Theory Vol. 167, (2022): 465-487.

"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.