Zhao, Tuo

96 publications

NeurIPS 2025 A Minimalist Example of Edge-of-Stability and Progressive Sharpening Liming Liu, Zixuan Zhang, Simon Shaolei Du, Tuo Zhao

NeurIPS 2025 AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders Yuezhou Hu, Jiaxin Guo, Xinyu Feng, Tuo Zhao

NeurIPS 2025 Ask a Strong LLM Judge When Your Reward Model Is Uncertain Zhenghao Xu, Qin Lu, Qingru Zhang, Liang Qiu, Ilgee Hong, Changlong Yu, Wenlin Yao, Yao Liu, Haoming Jiang, Lihong Li, Hyokun Yun, Tuo Zhao

ICML 2025 Deep Reinforcement Learning from Hierarchical Preference Design Alexander Bukharin, Yixiao Li, Pengcheng He, Tuo Zhao

ICML 2025 Discriminative Finetuning of Generative Large Language Models Without Reward Models and Human Preference Data Siqi Guo, Ilgee Hong, Vicente Balmaseda, Changlong Yu, Liang Qiu, Xin Liu, Haoming Jiang, Tuo Zhao, Tianbao Yang

ICLRW 2025 NoWag: A Unified Framework for Shape Preserving Compression of Large Language Models Lawrence Ray Liu, Inesh Chakrabarti, Yixiao Li, Mengdi Wang, Tuo Zhao, Lin Yang

NeurIPS 2025 Think-RM: Enabling Long-Horizon Reasoning in Generative Reward Models Ilgee Hong, Changlong Yu, Liang Qiu, Weixiang Yan, Zhenghao Xu, Haoming Jiang, Qingru Zhang, Qin Lu, Xin Liu, Chao Zhang, Tuo Zhao

NeurIPS 2024 Adaptive Preference Scaling for Reinforcement Learning with Human Feedback Ilgee Hong, Zichong Li, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao

ICML 2024 Beyond Point Prediction: Score Matching-Based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process Zichong Li, Qunzhi Xu, Zhenghao Xu, Yajun Mei, Tuo Zhao, Hongyuan Zha

JMLR 2024 Deep Nonparametric Estimation of Operators Between Infinite Dimensional Spaces Hao Liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao

ICLR 2024 LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models Yixiao Li, Yifan Yu, Chen Liang, Nikos Karampatziakis, Pengcheng He, Weizhu Chen, Tuo Zhao

NeurIPS 2024 Nonparametric Classification on Low Dimensional Manifolds Using Overparameterized Convolutional Residual Networks Zixuan Zhang, Kaiqi Zhang, Minshuo Chen, Yuma Takeda, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang

NeurIPS 2024 Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks Zhenghao Xu, Yuqing Wang, Tuo Zhao, Rachel Ward, Molei Tao

ICMLW 2024 RNR: Teaching Large Language Models to Follow Roles and Rules Kuan Wang, Alexander Bukharin, Haoming Jiang, Qingyu Yin, Zhengyang Wang, Tuo Zhao, Jingbo Shang, Chao Zhang, Bing Yin, Xian Li, Jianshu Chen, Shiyang Li

NeurIPS 2024 Robust Reinforcement Learning from Corrupted Human Feedback Alexander Bukharin, Ilgee Hong, Haoming Jiang, Zichong Li, Qingru Zhang, Zixuan Zhang, Tuo Zhao

JMLR 2024 Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds Zhenghao Xu, Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao

ICLR 2024 Tell Your Model Where to Attend: Post-Hoc Attention Steering for LLMs Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao

ICML 2024 To Cool or Not to Cool? Temperature Network Meets Large Foundation Models via DRO Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang

ICLR 2023 Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao

NeurIPSW 2023 DiP-GNN: Discriminative Pre-Training of Graph Neural Networks Simiao Zuo, Haoming Jiang, Qingyu Yin, Xianfeng Tang, Bing Yin, Tuo Zhao

ICML 2023 Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao

NeurIPSW 2023 Good Regularity Creates Large Learning Rate Implicit Biases: Edge of Stability, Balancing, and Catapult Yuqing Wang, Zhenghao Xu, Tuo Zhao, Molei Tao

NeurIPSW 2023 HART: Efficient Adaptation via Regularized Autoregressive Parameter Generation Chen Liang, Nikos Karampatziakis, Tuo Zhao, Weizhu Chen

ICLR 2023 HomoDistil: Homotopic Task-Agnostic Distillation of Pre-Trained Transformers Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bing Yin, Tuo Zhao

ICML 2023 Less Is More: Task-Aware Layer-Wise Distillation for Language Model Compression Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen, Tuo Zhao

ICML 2023 LoSparse: Structured Compression of Large Language Models Based on Low-Rank and Sparse Approximation Yixiao Li, Yifan Yu, Qingru Zhang, Chen Liang, Pengcheng He, Weizhu Chen, Tuo Zhao

ICML 2023 Machine Learning Force Fields with Data Cost Aware Training Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao

NeurIPSW 2023 Machine Learning Force Fields with Data Cost Aware Training Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao

NeurIPS 2023 Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms Shenao Zhang, Boyi Liu, Zhaoran Wang, Tuo Zhao

NeurIPS 2023 Module-Wise Adaptive Distillation for Multimodality Foundation Models Chen Liang, Jiahui Yu, Ming-Hsuan Yang, Matthew Brown, Yin Cui, Tuo Zhao, Boqing Gong, Tianyi Zhou

NeurIPSW 2023 Nonparametric Classification on Low Dimensional Manifolds Using Overparameterized Convolutional Residual Networks Zixuan Zhang, Kaiqi Zhang, Minshuo Chen, Yuma Takeda, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang

JMLR 2023 Pivotal Estimation of Linear Discriminant Analysis in High Dimensions Ethan X. Fang, Yajun Mei, Yuyang Shi, Qunzhi Xu, Tuo Zhao

AISTATS 2023 Reinforcement Learning for Adaptive Mesh Refinement Jiachen Yang, Tarik Dzanic, Brenden Petersen, Jun Kudo, Ketan Mittal, Vladimir Tomov, Jean-Sylvain Camier, Tuo Zhao, Hongyuan Zha, Tzanio Kolev, Robert Anderson, Daniel Faissol

NeurIPS 2023 Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao

ICML 2023 SMURF-THP: Score Matching-Based UnceRtainty quantiFication for Transformer Hawkes Process Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang, Tuo Zhao, Hongyuan Zha

ICLR 2023 Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds Using Deep Networks Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao

ICML 2023 Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang

NeurIPSW 2023 Tell Your Model Where to Attend: Post-Hoc Attention Steering for LLMs Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao

AISTATS 2022 Noise Regularizes Over-Parameterized Rank One Matrix Recovery, Provably Tianyi Liu, Yan Li, Enlu Zhou, Tuo Zhao

L4DC 2022 Adversarially Regularized Policy Learning Guided by Trajectory Optimization Zhigen Zhao, Simiao Zuo, Tuo Zhao, Ye Zhao

ICML 2022 Benefits of Overparameterized Convolutional Residual Networks: Function Approximation Under Smoothness Constraint Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao

NeurIPSW 2022 Benefits of Overparameterized Convolutional Residual Networks: Function Approximation Under Smoothness Constraint Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao

ICLR 2022 Frequency-Aware SGD for Efficient Embedding Learning with Provable Benefits Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan

ICLR 2022 Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao

ICLR 2022 No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao

NeurIPS 2022 On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds Biraj Dahal, Alexander Havrilla, Minshuo Chen, Tuo Zhao, Wenjing Liao

ICML 2022 PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao

ICLR 2022 Taming Sparsely Activated Transformer with Stochastic Experts Simiao Zuo, Xiaodong Liu, Jian Jiao, Young Jin Kim, Hany Hassan, Ruofei Zhang, Jianfeng Gao, Tuo Zhao

AISTATS 2021 Learning to Defend by Learning to Attack Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao

AISTATS 2021 Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization Tianyi Liu, Yan Li, Song Wei, Enlu Zhou, Tuo Zhao

ICLR 2021 A Hypergradient Approach to Robust Regression Without Correspondence Yujia Xie, Yixiu Mao, Simiao Zuo, Hongteng Xu, Xiaojing Ye, Tuo Zhao, Hongyuan Zha

ICML 2021 Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao

ICML 2021 How Important Is the Train-Validation Split in Meta-Learning? Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason Lee, Sham Kakade, Huan Wang, Caiming Xiong

NeurIPS 2021 Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL Minshuo Chen, Yan Li, Ethan Wang, Zhuoran Yang, Zhaoran Wang, Tuo Zhao

ICML 2020 Deep Reinforcement Learning with Robust and Smooth Policy Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao

NeurIPSW 2020 Differentiable Top-$k$ with Optimal Transport Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister

NeurIPS 2020 Differentiable Top-K with Optimal Transport Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister

ICLR 2020 Implicit Bias of Gradient Descent Based Adversarial Training on Separable Data Yan Li, Ethan X.Fang, Huan Xu, Tuo Zhao

ICLR 2020 On Computation and Generalization of Generative Adversarial Imitation Learning Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao

AISTATS 2020 On Generalization Bounds of a Family of Recurrent Neural Networks Minshuo Chen, Xingguo Li, Tuo Zhao

NeurIPS 2020 Towards Understanding Hierarchical Learning: Benefits of Neural Representations Minshuo Chen, Yu Bai, Jason Lee, Tuo Zhao, Huan Wang, Caiming Xiong, Richard Socher

ICML 2020 Transformer Hawkes Process Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha

NeurIPS 2020 Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? --- a Neural Tangent Kernel Perspective Kaixuan Huang, Yuqing Wang, Molei Tao, Tuo Zhao

NeurIPS 2019 Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao

ICLRW 2019 Learning to Defense by Learning to Attack Zhehui Chen, Haoming Jiang, Yuyang Shi, Bo Dai, Tuo Zhao

NeurIPS 2019 Meta Learning with Relational Information for Short Sequences Yujia Xie, Haoming Jiang, Feng Liu, Tuo Zhao, Hongyuan Zha

ICLR 2019 On Computation and Generalization of Generative Adversarial Networks Under Spectrum Control Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao

AISTATS 2019 On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition Zhehui Chen, Xingguo Li, Lin Yang, Jarvis Haupt, Tuo Zhao

UAI 2019 On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don’t Worry About Its Nonsmooth Loss Function Xinguo Li, Haoming Jiang, Jarvis Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao

ICML 2019 On Scalable and Efficient Computation of Large Scale Optimal Transport Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha

ICLRW 2019 On Scalable and Efficient Computation of Large Scale Optimal Transport Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha

UAI 2019 Online Factorization and Partition of Complex Networks by Random Walk Lin Yang, Zheng Yu, Vladimir Braverman, Tuo Zhao, Mengdi Wang

MLOSS 2019 Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao

ICML 2019 Toward Understanding the Importance of Noise in Training Neural Networks Mo Zhou, Tianyi Liu, Yan Li, Dachao Lin, Enlu Zhou, Tuo Zhao

NeurIPS 2019 Towards Understanding the Importance of Shortcut Connections in Residual Networks Tianyi Liu, Minshuo Chen, Mo Zhou, Simon S Du, Enlu Zhou, Tuo Zhao

NeurIPS 2018 Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization Minshuo Chen, Lin Yang, Mengdi Wang, Tuo Zhao

NeurIPS 2018 Provable Gaussian Embedding with One Observation Ming Yu, Zhuoran Yang, Tuo Zhao, Mladen Kolar, Zhaoran Wang

NeurIPS 2018 The Physical Systems Behind Optimization Algorithms Lin Yang, Raman Arora, Vladimir Braverman, Tuo Zhao

NeurIPS 2018 Towards Understanding Acceleration Tradeoff Between Momentum and Asynchrony in Nonconvex Stochastic Optimization Tianyi Liu, Shiyang Li, Jianping Shi, Enlu Zhou, Tuo Zhao

NeurIPS 2017 Deep Hyperspherical Learning Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhiding Yu, Bo Dai, Tuo Zhao, Le Song

NeurIPS 2017 On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning Xingguo Li, Lin Yang, Jason Ge, Jarvis Haupt, Tong Zhang, Tuo Zhao

ICML 2017 Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability Zhehui Chen, Lin F. Yang, Chris Junchi Li, Tuo Zhao

NeurIPS 2017 Parametric Simplex Method for Sparse Learning Haotian Pang, Han Liu, Robert J Vanderbei, Tuo Zhao

AISTATS 2016 An Improved Convergence Analysis of Cyclic Block Coordinate Descent-Type Methods for Strongly Convex Minimization Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong

NeurIPS 2016 NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization Davood Hajinezhad, Mingyi Hong, Tuo Zhao, Zhaoran Wang

ICML 2016 Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis Haupt

NeurIPS 2015 A Nonconvex Optimization Framework for Low Rank Matrix Estimation Tuo Zhao, Zhaoran Wang, Han Liu

JMLR 2015 Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery Han Liu, Lie Wang, Tuo Zhao

MLOSS 2015 The Flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R Xingguo Li, Tuo Zhao, Xiaoming Yuan, Han Liu

NeurIPS 2014 Accelerated Mini-Batch Randomized Block Coordinate Descent Method Tuo Zhao, Mo Yu, Yiming Wang, Raman Arora, Han Liu

NeurIPS 2014 Multivariate Regression with Calibration Han Liu, Lie Wang, Tuo Zhao

JMLR 2013 CODA: High Dimensional Copula Discriminant Analysis Fang Han, Tuo Zhao, Han Liu

NeurIPS 2013 Sparse Inverse Covariance Estimation with Calibration Tuo Zhao, Han Liu

NeurIPS 2012 Smooth-Projected Neighborhood Pursuit for High-Dimensional Nonparanormal Graph Estimation Tuo Zhao, Kathryn Roeder, Han Liu

AISTATS 2012 Sparse Additive Machine Tuo Zhao, Han Liu

MLOSS 2012 The Huge Package for High-Dimensional Undirected Graph Estimation in R Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty, Larry Wasserman