Ying, Lexing

31 publications

UAI 2025 COS-DPO: Conditioned One-Shot Multi-Objective Fine-Tuning Framework Yinuo Ren, Tesi Xiao, Michael Shavlovsky, Lexing Ying, Holakou Rahmanian

NeurIPS 2025 Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms Yinuo Ren, Haoxuan Chen, Yuchen Zhu, Wei Guo, Yongxin Chen, Grant M. Rotskoff, Molei Tao, Lexing Ying

ICLRW 2025 Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms Yinuo Ren, Haoxuan Chen, Yuchen Zhu, Wei Guo, Yongxin Chen, Grant M. Rotskoff, Molei Tao, Lexing Ying

ICLR 2025 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

ICLRW 2025 Sampling on Metric Graphs Rajat Vadiraj Dwaraknath, Lexing Ying

NeurIPS 2024 Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity Haoxuan Chen, Yinuo Ren, Lexing Ying, Grant M. Rotskoff

ICLR 2024 Accelerating Sinkhorn Algorithm with Sparse Newton Iterations Xun Tang, Michael Shavlovsky, Holakou Rahmanian, Elisa Tardini, Kiran Koshy Thekumparampil, Tesi Xiao, Lexing Ying

NeurIPSW 2024 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

NeurIPSW 2024 HyperDPO: Conditioned One-Shot Multi-Objective Fine-Tuning Framework Yinuo Ren, Tesi Xiao, Michael Shavlovsky, Lexing Ying, Holakou Rahmanian

AISTATS 2024 Multi-Objective Optimization via Wasserstein-Fisher-Rao Gradient Flow Yinuo Ren, Tesi Xiao, Tanmay Gangwani, Anshuka Rangi, Holakou Rahmanian, Lexing Ying, Subhajit Sanyal

ICML 2024 Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty Kaizhao Liu, Jose Blanchet, Lexing Ying, Yiping Lu

AAAI 2024 Statistical Spatially Inhomogeneous Diffusion Inference Yinuo Ren, Yiping Lu, Lexing Ying, Grant M. Rotskoff

AISTATS 2024 Understanding the Generalization Benefits of Late Learning Rate Decay Yinuo Ren, Chao Ma, Lexing Ying

ICLRW 2023 Bayesian Regularization of Empirical MDPs Samarth Gupta, Daniel N. Hill, Lexing Ying, Inderjit S Dhillon

JMLR 2023 Continuous-in-Time Limit for Bayesian Bandits Yuhua Zhu, Zachary Izzo, Lexing Ying

ICLR 2023 Minimax Optimal Kernel Operator Learning via Multilevel Training Jikai Jin, Yiping Lu, Jose Blanchet, Lexing Ying

NeurIPSW 2023 On Optimization Formulations of Finite Horizon MDPs Rajat Vadiraj Dwaraknath, Lexing Ying

NeurIPS 2023 When Can Regression-Adjusted Control Variate Help? Rare Events, Sobolev Embedding and Minimax Optimality Jose Blanchet, Haoxuan Chen, Yiping Lu, Lexing Ying

AISTATS 2022 How to Learn When Data Gradually Reacts to Your Model Zachary Izzo, James Zou, Lexing Ying

ICLR 2022 Machine Learning for Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality Yiping Lu, Haoxuan Chen, Jianfeng Lu, Lexing Ying, Jose Blanchet

NeurIPSW 2022 Minimax Optimal Kernel Operator Learning via Multilevel Training Jikai Jin, Yiping Lu, Jose Blanchet, Lexing Ying

ICLR 2022 Provably Convergent Quasistatic Dynamics for Mean-Field Two-Player Zero-Sum Games Chao Ma, Lexing Ying

NeurIPS 2022 Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent Yiping Lu, Jose Blanchet, Lexing Ying

NeurIPSW 2022 Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls Yiping Lu, Jiajin Li, Lexing Ying, Jose Blanchet

ICML 2021 How to Learn When Data Reacts to Your Model: Performative Gradient Descent Zachary Izzo, Lexing Ying, James Zou

NeurIPS 2021 On Linear Stability of SGD and Input-Smoothness of Neural Networks Chao Ma, Lexing Ying

NeurIPSW 2021 Statistical Numerical PDE : Fast Rate, Neural Scaling Law and When It’s Optimal Yiping Lu, Haoxuan Chen, Jianfeng Lu, Lexing Ying, Jose Blanchet

ICML 2021 Top-K eXtreme Contextual Bandits with Arm Hierarchy Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean Foster, Daniel N Hill, Inderjit S. Dhillon

ICLR 2021 Why Resampling Outperforms Reweighting for Correcting Sampling Bias with Stochastic Gradients Jing An, Lexing Ying, Yuhua Zhu

ICML 2020 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

ICLRW 2020 A Mean-Field Analysis of Deep ResNet and Beyond:Towards Provable Optimization via Overparameterization from Depth Yiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu, Lexing Ying