| 2025 | ICLR | How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework. | Yinuo Ren, Haoxuan Chen, Grant M. Rotskoff, Lexing Ying |
| 2025 | UAI | COS-DPO: Conditioned One-Shot Multi-Objective Fine-Tuning Framework. | Yinuo Ren, Tesi Xiao, Michael Shavlovsky, Lexing Ying, Holakou Rahmanian |
| 2024 | AAAI | Statistical Spatially Inhomogeneous Diffusion Inference. | Yinuo Ren, Yiping Lu, Lexing Ying, Grant M. Rotskoff |
| 2024 | AISTATS | Understanding the Generalization Benefits of Late Learning Rate Decay. | Yinuo Ren, Chao Ma, Lexing Ying |
| 2024 | AISTATS | Multi-objective Optimization via Wasserstein-Fisher-Rao Gradient Flow. | Yinuo Ren, Tesi Xiao, Tanmay Gangwani, Anshuka Rangi, Holakou Rahmanian, Lexing Ying, Subhajit Sanyal |
| 2024 | ICLR | Accelerating Sinkhorn algorithm with sparse Newton iterations. | Xun Tang, Michael Shavlovsky, Holakou Rahmanian, Elisa Tardini, Kiran Koshy Thekumparampil, Tesi Xiao, Lexing Ying |
| 2024 | ICML | Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty. | Kaizhao Liu, Jos H. Blanchet, Lexing Ying, Yiping Lu |
| 2023 | ICLR | Minimax Optimal Kernel Operator Learning via Multilevel Training. | Jikai Jin, Yiping Lu, Jos H. Blanchet, Lexing Ying |
| 2022 | AISTATS | How to Learn when Data Gradually Reacts to Your Model. | Zachary Izzo, James Zou, Lexing Ying |
| 2022 | ICLR | Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality. | Yiping Lu, Haoxuan Chen, Jianfeng Lu, Lexing Ying, Jose H. Blanchet |
| 2022 | ICLR | Provably convergent quasistatic dynamics for mean-field two-player zero-sum games. | Chao Ma, Lexing Ying |
| 2022 | WWW | Enterprise-Scale Search: Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees. | Philip A. Etter, Kai Zhong, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon |
| 2021 | ICLR | Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients. | Jing An, Lexing Ying, Yuhua Zhu |
| 2021 | ICML | How to Learn when Data Reacts to Your Model: Performative Gradient Descent. | Zachary Izzo, Lexing Ying, James Zou |
| 2021 | ICML | Top-k eXtreme Contextual Bandits with Arm Hierarchy. | Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean P. Foster, Daniel N. Hill, Inderjit S. Dhillon |
| 2020 | ICML | A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth. | Yiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu, Lexing Ying |
| 2009 | SC | A massively parallel adaptive fast-multipole method on heterogeneous architectures. | Ilya Lashuk, Aparna Chandramowlishwaran, Harper Langston, Tuan-Anh Nguyen, Rahul S. Sampath, Aashay Shringarpure, Richard W. Vuduc, Lexing Ying, Denis Zorin, George Biros |
| 2003 | SC | A New Parallel Kernel-Independent Fast Multipole Method. | Lexing Ying, George Biros, Denis Zorin, Harper Langston |