Haihao Lu - RankMe

51 papers A* 8A 2B 1Journal 40

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Practical and Optimal First-Order Method for Large-Scale Convex Quadratic Programming. Math. Program. Haihao Lu, Jinwen Yang
2026	J	`jnl`	On the Sparsity of Optimal Linear Decision Rules for a Class of Robust Optimization Problems with Box Uncertainty Sets. Oper. Res. Haihao Lu, Bradley Sturt
2025	J	`jnl`	On the geometry and refined rate of primal-dual hybrid gradient for linear programming. Math. Program. Haihao Lu, Jinwen Yang
2025	J	`jnl`	Optimizing Scalable Targeted Marketing Policies with Constraints. Mark. Sci. Haihao Lu, Duncan Simester, Yuting Zhu
2025	J	`jnl`	Regularized Online Allocation Problems: Fairness and Beyond. Manuf. Serv. Oper. Manag. Santiago R. Balseiro, Haihao Lu, Vahab Mirrokni
2025	J	`jnl`	cuPDLP.jl: A GPU Implementation of Restarted Primal-Dual Hybrid Gradient for Linear Programming in Julia. Oper. Res. Haihao Lu, Jinwen Yang
2024	A*	`conf`	A Field Guide for Pacing Budget and ROS Constraints. ICML Santiago R. Balseiro, Kshipra Bhawalkar, Zhe Feng, Haihao Lu, Vahab Mirrokni, Balasubramanian Sivan, Di Wang
2024	J	`jnl`	A J-symmetric quasi-newton method for minimax problems. Math. Program. Azam Asl, Haihao Lu, Jinwen Yang
2024	J	`jnl`	Auto-Bidding and Auctions in Online Advertising: A Survey. SIGecom Exch. Gagan Aggarwal, Ashwinkumar Badanidiyuru, Santiago R. Balseiro, Kshipra Bhawalkar, Yuan Deng, Zhe Feng, Gagan Goel, Christopher Liaw, Haihao Lu, Mohammad Mahdian, Jieming Mao, Aranyak Mehta, Vahab Mirrokni, Renato Paes Leme, Andrés Perlroth, Georgios Piliouras, Jon Schneider, Ariel Schvartzman, Balasubramanian Sivan, Kelly Spendlove, Yifeng Teng, Di Wang, Hanrui Zhang, Mingfei Zhao, Wennan Zhu, Song Zuo
2024	J	`jnl`	Auto-bidding and Auctions in Online Advertising: A Survey. CoRR Gagan Aggarwal, Ashwinkumar Badanidiyuru, Santiago R. Balseiro, Kshipra Bhawalkar, Yuan Deng, Zhe Feng, Gagan Goel, Christopher Liaw, Haihao Lu, Mohammad Mahdian, Jieming Mao, Aranyak Mehta, Vahab Mirrokni, Renato Paes Leme, Andrés Perlroth, Georgios Piliouras, Jon Schneider, Ariel Schvartzman, Balasubramanian Sivan, Kelly Spendlove, Yifeng Teng, Di Wang, Hanrui Zhang, Mingfei Zhao, Wennan Zhu, Song Zuo
2024	J	`jnl`	Infeasibility Detection with Primal-Dual Hybrid Gradient for Large-Scale Linear Programming. SIAM J. Optim. David L. Applegate, Mateo Díaz, Haihao Lu, Miles Lubin
2024	J	`jnl`	MPAX: Mathematical Programming in JAX. CoRR Haihao Lu, Zedong Peng, Jinwen Yang
2024	J	`jnl`	On the Linear Convergence of Extragradient Methods for Nonconvex-Nonconcave Minimax Problems. INFORMS J. Optim. Saeed Hajizadeh, Haihao Lu, Benjamin Grimmer
2023	J	`jnl`	Faster first-order primal-dual methods for linear programming using restarts and sharpness. Math. Program. David L. Applegate, Oliver Hinder, Haihao Lu, Miles Lubin
2023	J	`jnl`	Joint Feedback Loop for Spend and Return-On-Spend Constraints. CoRR Santiago R. Balseiro, Kshipra Bhawalkar, Zhe Feng, Haihao Lu, Vahab Mirrokni, Balasubramanian Sivan, Di Wang
2023	A*	`conf`	Online Ad Procurement in Non-stationary Autobidding Worlds. NeurIPS Jason Cheuk Nam Liang, Haihao Lu, Baoyu Zhou
2023	J	`jnl`	Online Ad Procurement in Non-stationary Autobidding Worlds. CoRR Jason Cheuk Nam Liang, Haihao Lu, Baoyu Zhou
2023	J	`jnl`	The Best of Many Worlds: Dual Mirror Descent for Online Allocation Problems. Oper. Res. Santiago R. Balseiro, Haihao Lu, Vahab Mirrokni
2023	J	`jnl`	The landscape of the proximal point method for nonconvex-nonconcave minimax optimization. Math. Program. Benjamin Grimmer, Haihao Lu, Pratik Worah, Vahab Mirrokni
2022	J	`jnl`	A J-Symmetric Quasi-Newton Method for Minimax Problems. CoRR Azam Asl, Haihao Lu
2022	J	`jnl`	An O(s Math. Program. Haihao Lu
2022	J	`jnl`	Frank-Wolfe Methods with an Unbounded Feasible Region and Applications to Structured Learning. SIAM J. Optim. Haoyue Wang, Haihao Lu, Rahul Mazumder
2022	J	`jnl`	From Online Optimization to PID Controllers: Mirror Descent with Momentum. CoRR Santiago R. Balseiro, Haihao Lu, Vahab S. Mirrokni, Balasubramanian Sivan
2022	B	`conf`	Limiting Behaviors of Nonconvex-Nonconcave Minimax Optimization via Continuous-Time Systems. ALT Benjamin Grimmer, Haihao Lu, Pratik Worah, Vahab S. Mirrokni
2021	J	`jnl`	Generalized stochastic Frank-Wolfe algorithm with stochastic "substitute" gradient for structured convex optimization. Math. Program. Haihao Lu, Robert M. Freund
2021	J	`jnl`	Linear Convergence of Stochastic Primal Dual Methods for Linear Programming Using Variance Reduction and Restarts. CoRR Haihao Lu, Jinwen Yang
2021	A*	`conf`	Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient. NeurIPS David L. Applegate, Mateo Díaz, Oliver Hinder, Haihao Lu, Miles Lubin, Brendan O'Donoghue, Warren Schudy
2021	A*	`conf`	Regularized Online Allocation Problems: Fairness and Beyond. ICML Santiago R. Balseiro, Haihao Lu, Vahab S. Mirrokni
2020	A	`conf`	Accelerating Gradient Boosting Machines. AISTATS Haihao Lu, Sai Praneeth Karimireddy, Natalia Ponomareva, Vahab S. Mirrokni
2020	J	`jnl`	An O(s CoRR Haihao Lu
2020	A*	`conf`	Contextual Reserve Price Optimization in Auctions via Mixed Integer Programming. NeurIPS Joey Huchette, Haihao Lu, Hossein Esfandiari, Vahab S. Mirrokni
2020	J	`jnl`	Contextual Reserve Price Optimization in Auctions. CoRR Joey Huchette, Haihao Lu, Hossein Esfandiari, Vahab S. Mirrokni
2020	A*	`conf`	Dual Mirror Descent for Online Allocation Problems. ICML Santiago R. Balseiro, Haihao Lu, Vahab S. Mirrokni
2020	J	`jnl`	Limiting Behaviors of Nonconvex-Nonconcave Minimax Optimization via Continuous-Time Systems. CoRR Benjamin Grimmer, Haihao Lu, Pratik Worah, Vahab S. Mirrokni
2020	A	`conf`	Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization. AISTATS Kenji Kawaguchi, Haihao Lu
2020	J	`jnl`	Randomized Gradient Boosting Machine. SIAM J. Optim. Haihao Lu, Rahul Mazumder
2020	J	`jnl`	Regularized Online Allocation Problems: Fairness and Beyond. CoRR Santiago R. Balseiro, Haihao Lu, Vahab S. Mirrokni
2020	J	`jnl`	The Best of Many Worlds: Dual Mirror Descent for Online Allocation Problems. CoRR Santiago R. Balseiro, Haihao Lu, Vahab S. Mirrokni
2020	J	`jnl`	The Landscape of Nonconvex-Nonconcave Minimax Optimization. CoRR Benjamin Grimmer, Haihao Lu, Pratik Worah, Vahab S. Mirrokni
2019	J	`jnl`	"Relative Continuity" for Non-Lipschitz Nonsmooth Convex Optimization Using Stochastic (or Deterministic) Mirror Descent. INFORMS J. Optim. Haihao Lu
2019	J	`jnl`	A Stochastic First-Order Method for Ordered Empirical Risk Minimization. CoRR Kenji Kawaguchi, Haihao Lu
2019	J	`jnl`	Accelerating Gradient Boosting Machine. CoRR Haihao Lu, Sai Praneeth Karimireddy, Natalia Ponomareva, Vahab S. Mirrokni
2018	A*	`conf`	Accelerating Greedy Coordinate Descent Methods. ICML Haihao Lu, Robert M. Freund, Vahab S. Mirrokni
2018	A*	`conf`	Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions. ICML Shuaiwen Wang, Wenda Zhou, Haihao Lu, Arian Maleki, Vahab S. Mirrokni
2018	J	`jnl`	Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions. CoRR Shuaiwen Wang, Wenda Zhou, Haihao Lu, Arian Maleki, Vahab S. Mirrokni
2018	J	`jnl`	Approximate Leave-One-Out for High-Dimensional Non-Differentiable Learning Problems. CoRR Shuaiwen Wang, Wenda Zhou, Arian Maleki, Haihao Lu, Vahab S. Mirrokni
2018	J	`jnl`	Near-Optimal Online Knapsack Strategy for Real-Time Bidding in Internet Advertising. CoRR Jonathan Amar, Nicholas Renegar, Haihao Lu
2018	J	`jnl`	New computational guarantees for solving convex optimization problems with first order methods, via a function growth condition measure. Math. Program. Robert M. Freund, Haihao Lu
2018	J	`jnl`	Randomized Gradient Boosting Machine. CoRR Haihao Lu, Rahul Mazumder
2018	J	`jnl`	Relatively Smooth Convex Optimization by First-Order Methods, and Applications. SIAM J. Optim. Haihao Lu, Robert M. Freund, Yurii E. Nesterov
2017	J	`jnl`	Depth Creates No Bad Local Minima. CoRR Haihao Lu, Kenji Kawaguchi