Quanquan Gu

ORCID

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 317

Top Venues

Publications

Xuheng Li, Yihe Deng, Jingfeng Wu, Dongruo Zhou, Quanquan Gu
Risk Bounds of Accelerated SGD for Overparameterized Linear Regression. ICLR (2024)
Yue Wu, Zhiqing Sun, Huizhuo Yuan, Kaixuan Ji, Yiming Yang, Quanquan Gu
Self-Play Preference Optimization for Language Model Alignment. CoRR (2024)
Zixiang Chen, Yihe Deng, Huizhuo Yuan, Kaixuan Ji, Quanquan Gu
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models. CoRR (2024)
Dongruo Zhou, Jinghui Chen, Yuan Cao, Ziyan Yang, Quanquan Gu
On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization. Trans. Mach. Learn. Res. 2024 (2024)
Zijie Huang, Jeehyun Hwang, Junkai Zhang, Jinwoo Baik, Weitong Zhang, Dominik Wodarz, Yizhou Sun, Quanquan Gu, Wei Wang
Causal Graph ODE: Continuous Treatment Effect Modeling in Multi-agent Dynamical Systems. WWW (2024)
Qiwei Di, Jiafan He, Dongruo Zhou, Quanquan Gu
Nearly Minimax Optimal Regret for Learning Linear Mixture Stochastic Shortest Path. CoRR (2024)
Qiwei Di, Tao Jin, Yue Wu, Heyang Zhao, Farzad Farnoud, Quanquan Gu
Variance-aware Regret Bounds for Stochastic Contextual Dueling Bandits. ICLR (2024)
Xiwei Cheng, Xiangxin Zhou, Yuwei Yang, Yu Bao, Quanquan Gu
Decomposed Direct Preference Optimization for Structure-Based Drug Design. CoRR (2024)
Xiangxin Zhou, Xiwei Cheng, Yuwei Yang, Yu Bao, Liang Wang, Quanquan Gu
DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization. CoRR (2024)
Weitong Zhang, Zhiyuan Fan, Jiafan He, Quanquan Gu
Settling Constant Regrets in Linear Markov Decision Processes. CoRR (2024)
Linxi Zhao, Yihe Deng, Weitong Zhang, Quanquan Gu
Mitigating Object Hallucination in Large Vision-Language Models via Classifier-Free Guidance. CoRR (2024)
Xiangxin Zhou, Xiwei Cheng, Yuwei Yang, Yu Bao, Liang Wang, Quanquan Gu
DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization. ICLR (2024)
Qiwei Di, Jiafan He, Quanquan Gu
Nearly Optimal Algorithms for Contextual Dueling Bandits from Adversarial Feedback. CoRR (2024)
Yan Wang, Lihao Wang, Yuning Shen, Yiqun Wang, Huizhuo Yuan, Yue Wu, Quanquan Gu
Protein Conformation Generation via Force-Guided SE(3) Diffusion Models. CoRR (2024)
Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Peter L. Bartlett
How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression? ICLR (2024)
Huizhuo Yuan, Zixiang Chen, Kaixuan Ji, Quanquan Gu
Self-Play Fine-Tuning of Diffusion Models for Text-to-Image Generation. CoRR (2024)
Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chao Zhang, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao
TrustLLM: Trustworthiness in Large Language Models. CoRR (2024)
Kaixuan Ji, Qingyue Zhao, Jiafan He, Weitong Zhang, Quanquan Gu
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs. ICLR (2024)
Qiwei Di, Heyang Zhao, Jiafan He, Quanquan Gu
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning. ICLR (2024)
Kaixuan Ji, Jiafan He, Quanquan Gu
Reinforcement Learning from Human Feedback with Active Queries. CoRR (2024)
Zijie Huang, Jeehyun Hwang, Junkai Zhang, Jinwoo Baik, Weitong Zhang, Dominik Wodarz, Yizhou Sun, Quanquan Gu, Wei Wang
Causal Graph ODE: Continuous Treatment Effect Modeling in Multi-agent Dynamical Systems. CoRR (2024)
Xinyou Wang, Zaixiang Zheng, Fei Ye, Dongyu Xue, Shujian Huang, Quanquan Gu
Diffusion Language Models Are Versatile Protein Learners. CoRR (2024)
Junkai Zhang, Weitong Zhang, Dongruo Zhou, Quanquan Gu
Uncertainty-Aware Reward-Free Exploration with General Function Approximation. CoRR (2024)
Yiwen Kou, Zixiang Chen, Quanquan Gu, Sham M. Kakade
Matching the Statistical Query Lower Bound for k-sparse Parity Problems with Stochastic Gradient Descent. CoRR (2024)
Xiangxin Zhou, Dongyu Xue, Ruizhe Chen, Zaixiang Zheng, Liang Wang, Quanquan Gu
Antigen-Specific Antibody Design via Direct Energy-based Preference Optimization. CoRR (2024)
Chenlu Ye, Jiafan He, Quanquan Gu, Tong Zhang
Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption. CoRR (2024)
Xuheng Li, Heyang Zhao, Quanquan Gu
Feel-Good Thompson Sampling for Contextual Dueling Bandits. CoRR (2024)
Jiaqi Guan, Xiangxin Zhou, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, Quanquan Gu
DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design. CoRR (2024)
Zixiang Chen, Jun Han, Yongqian Li, Yiwen Kou, Eran Halperin, Robert E. Tillman, Quanquan Gu
Guided Discrete Diffusion for Electronic Health Record Generation. CoRR (2024)
Zixiang Chen, Yihe Deng, Yuanzhi Li, Quanquan Gu
Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP. ICLR (2024)
Yue Wu, Tao Jin, Hao Lou, Farzad Farnoud, Quanquan Gu
Borda Regret Minimization for Generalized Linear Dueling Bandits. CoRR (2023)
Zaixiang Zheng, Yifan Deng, Dongyu Xue, Yi Zhou, Fei Ye, Quanquan Gu
Structure-informed Language Models Are Protein Designers. ICML (2023)
Yue Wu, Shuaicheng Zhang, Wenchao Yu, Yanchi Liu, Quanquan Gu, Dawei Zhou, Haifeng Chen, Wei Cheng
Personalized Federated Learning under Mixture of Distributions. ICML (2023)
Jiafan He, Heyang Zhao, Dongruo Zhou, Quanquan Gu
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes. ICML (2023)
Difan Zou, Yuan Cao, Yuanzhi Li, Quanquan Gu
The Benefits of Mixup for Feature Learning. ICML (2023)
Jinghui Chen, Yuan Cao, Quanquan Gu
Benign Overfitting in Adversarially Robust Linear Classification. UAI (2023)
Chris Junchi Li, Huizhuo Yuan, Gauthier Gidel, Quanquan Gu, Michael I. Jordan
Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization. ICML (2023)
Yiwen Kou, Zixiang Chen, Quanquan Gu
Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data. CoRR (2023)
Heyang Zhao, Jiafan He, Quanquan Gu
A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation. CoRR (2023)
Junkai Zhang, Weitong Zhang, Quanquan Gu
Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs. CoRR (2023)
Yiwen Kou, Zixiang Chen, Yuanzhou Chen, Quanquan Gu
Benign Overfitting in Two-layer ReLU Convolutional Neural Networks. ICML (2023)
Angela Yuan, Chris Junchi Li, Gauthier Gidel, Michael I. Jordan, Quanquan Gu, Simon S. Du
Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure. NeurIPS (2023)
Zaixiang Zheng, Yifan Deng, Dongyu Xue, Yi Zhou, Fei YE, Quanquan Gu
Structure-informed Language Models Are Protein Designers. CoRR (2023)
Yiwen Kou, Zixiang Chen, Quanquan Gu
Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data. NeurIPS (2023)
Lingxiao Wang, Bargav Jayaraman, David Evans, Quanquan Gu
Efficient Privacy-Preserving Stochastic Nonconvex Optimization. UAI (2023)
Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Peter L. Bartlett
How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression? CoRR (2023)
Yiwen Kou, Zixiang Chen, Yuan Cao, Quanquan Gu
How Does Semi-supervised Learning with Pseudo-labelers Work? A Case Study. ICLR (2023)
Chenlu Ye, Rui Yang, Quanquan Gu, Tong Zhang
Corruption-Robust Offline Reinforcement Learning with General Function Approximation. CoRR (2023)
Xuheng Li, Yihe Deng, Jingfeng Wu, Dongruo Zhou, Quanquan Gu
Risk Bounds of Accelerated SGD for Overparameterized Linear Regression. CoRR (2023)
Zixiang Chen, Chris Junchi Li, Huizhuo Yuan, Quanquan Gu, Michael I. Jordan
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning. ICLR (2023)
Zichen Wang, Chuanhao Li, Chenyu Song, Lianghui Wang, Quanquan Gu, Huazheng Wang
Pure Exploration in Asynchronous Federated Bandits. CoRR (2023)
Zixiang Chen, Yihe Deng, Yuanzhi Li, Quanquan Gu
Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP. CoRR (2023)
Difan Zou, Yuan Cao, Yuanzhi Li, Quanquan Gu
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization. ICLR (2023)
Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency. CoRR (2023)
Yiwen Kou, Zixiang Chen, Yuanzhou Chen, Quanquan Gu
Benign Overfitting for Two-layer ReLU Networks. CoRR (2023)
Qiwei Di, Heyang Zhao, Jiafan He, Quanquan Gu
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning. CoRR (2023)
Weitong Zhang, Jiafan He, Zhiyuan Fan, Quanquan Gu
On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits. CoRR (2023)
Zixiang Chen, Huizhuo Yuan, Yongqian Li, Yiwen Kou, Junkai Zhang, Quanquan Gu
Fast Sampling via De-randomization for Discrete Diffusion Models. CoRR (2023)
Zixiang Chen, Junkai Zhang, Yiwen Kou, Xiangning Chen, Cho-Jui Hsieh, Quanquan Gu
Why Does Sharpness-Aware Minimization Generalize Better Than SGD? NeurIPS (2023)
Yue Wu, Jiafan He, Quanquan Gu
Uniform-PAC Guarantees for Model-Based RL with Bounded Eluder Dimension. UAI (2023)
Jiaqi Guan, Xiangxin Zhou, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, Quanquan Gu
DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design. ICML (2023)
Weitong Zhang, Jiafan He, Dongruo Zhou, Amy Zhang, Quanquan Gu
Provably efficient representation selection in Low-rank Markov Decision Processes: from online to offline RL. UAI (2023)
Yihe Deng, Weitong Zhang, Zixiang Chen, Quanquan Gu
Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves. CoRR (2023)
Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency. COLT (2023)
Quanquan Gu, Zhaoran Wang, Han Liu
Sparse PCA with Oracle Property. CoRR (2023)
Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Sham M. Kakade
Learning High-Dimensional Single-Neuron ReLU Networks with Finite Samples. CoRR (2023)
Yihe Deng, Yu Yang, Baharan Mirzasoleiman, Quanquan Gu
Robust Learning with Progressive Data Expansion Against Spurious Correlation. NeurIPS (2023)
Jiasheng Ye, Zaixiang Zheng, Yu Bao, Lihua Qian, Quanquan Gu
Diffusion Language Models Can Perform Many Tasks with Scaling and Instruction-Finetuning. CoRR (2023)
Yihe Deng, Yu Yang, Baharan Mirzasoleiman, Quanquan Gu
Robust Learning with Progressive Data Expansion Against Spurious Correlation. CoRR (2023)
Yuan Cao, Difan Zou, Yuanzhi Li, Quanquan Gu
The Implicit Bias of Batch Normalization in Linear Models and Two-layer Linear Convolutional Neural Networks. COLT (2023)
Junkai Zhang, Weitong Zhang, Quanquan Gu
Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs. ICML (2023)
Kaixuan Ji, Qingyue Zhao, Jiafan He, Weitong Zhang, Quanquan Gu
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs. CoRR (2023)
Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang
Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes. ICML (2023)
Yue Wu, Jiafan He, Quanquan Gu
Uniform-PAC Guarantees for Model-Based RL with Bounded Eluder Dimension. CoRR (2023)
Yuan Cao, Difan Zou, Yuanzhi Li, Quanquan Gu
The Implicit Bias of Batch Normalization in Linear Models and Two-layer Linear Convolutional Neural Networks. CoRR (2023)
Chen Ling, Xujiang Zhao, Jiaying Lu, Chengyuan Deng, Can Zheng, Junxiang Wang, Tanmoy Chowdhury, Yun Li, Hejie Cui, Xuchao Zhang, Tianjiao Zhao, Amit Panalkar, Wei Cheng, Haoyu Wang, Yanchi Liu, Zhengzhang Chen, Haifeng Chen, Chris White, Quanquan Gu, Carl Yang, Liang Zhao
Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models. CoRR (2023)
Zixiang Chen, Junkai Zhang, Yiwen Kou, Xiangning Chen, Cho-Jui Hsieh, Quanquan Gu
Why Does Sharpness-Aware Minimization Generalize Better Than SGD? CoRR (2023)
Difan Zou, Yuan Cao, Yuanzhi Li, Quanquan Gu
The Benefits of Mixup for Feature Learning. CoRR (2023)
Qiwei Di, Tao Jin, Yue Wu, Heyang Zhao, Farzad Farnoud, Quanquan Gu
Variance-Aware Regret Bounds for Stochastic Contextual Dueling Bandits. CoRR (2023)
Qiwei Di, Jiafan He, Dongruo Zhou, Quanquan Gu
Nearly Minimax Optimal Regret for Learning Linear Mixture Stochastic Shortest Path. ICML (2023)
Heyang Zhao, Dongruo Zhou, Jiafan He, Quanquan Gu
Optimal Online Generalized Linear Regression with Stochastic Noise and Its Application to Heteroscedastic Bandits. ICML (2023)
Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Sham M. Kakade
Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron. ICML (2023)
Xinzhe Zuo, Zixiang Chen, Huaxiu Yao, Yuan Cao, Quanquan Gu
Understanding Train-Validation Split in Meta-Learning with Neural Networks. ICLR (2023)
Chenlu Ye, Rui Yang, Quanquan Gu, Tong Zhang
Corruption-Robust Offline Reinforcement Learning with General Function Approximation. NeurIPS (2023)
Yue Wu, Shuaicheng Zhang, Wenchao Yu, Yanchi Liu, Quanquan Gu, Dawei Zhou, Haifeng Chen, Wei Cheng
Personalized Federated Learning under Mixture of Distributions. CoRR (2023)
Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. ICML (2023)
Weitong Zhang, Jiafan He, Zhiyuan Fan, Quanquan Gu
On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits. ICML (2023)
Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. CoRR (2023)
Hao Lou, Tao Jin, Yue Wu, Pan Xu, Quanquan Gu, Farzad Farnoud
Active Ranking without Strong Stochastic Transitivity. NeurIPS (2022)
Yue Wu, Dongruo Zhou, Quanquan Gu
Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation. AISTATS (2022)
Jinghui Chen, Yu Cheng, Zhe Gan, Quanquan Gu, Jingjing Liu
Efficient Robust Training via Backward Smoothing. AAAI (2022)
Heyang Zhao, Dongruo Zhou, Jiafan He, Quanquan Gu
Bandit Learning with General Function Classes: Heteroscedastic Noise and Variance-dependent Regret Bounds. CoRR (2022)
Yihan Wang, Zhouxing Shi, Quanquan Gu, Cho-Jui Hsieh
On the Convergence of Certified Robust Training with Interval Bound Propagation. CoRR (2022)
Zixiang Chen, Dongruo Zhou, Quanquan Gu
Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov Games. ALT (2022)
Dongruo Zhou, Quanquan Gu
Dimension-free Complexity Bounds for High-order Nonconvex Finite-sum Optimization. ICML (2022)
Yue Wu, Tao Jin, Hao Lou, Pan Xu, Farzad Farnoud, Quanquan Gu
Adaptive Sampling for Heterogeneous Rank Aggregation from Noisy Pairwise Comparisons. AISTATS (2022)
Zixiang Chen, Yihe Deng, Yue Wu, Quanquan Gu, Yuanzhi Li
Towards Understanding Mixture of Experts in Deep Learning. CoRR (2022)
Chris Junchi Li, Dongruo Zhou, Quanquan Gu, Michael I. Jordan
Learning Two-Player Mixture Markov Games: Kernel Function Approximation and Correlated Equilibrium. CoRR (2022)
Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Sham M. Kakade
Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime. NeurIPS (2022)
Pan Xu, Zheng Wen, Handong Zhao, Quanquan Gu
Neural Contextual Bandits with Deep Representation and Shallow Exploration. ICLR (2022)

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Publication Activity (10 Years)

Top Topics

Top Venues

Quanquan Gu