Tong Zhang

ORCID

Publication Activity (10 Years)

Years Active: 1996-2024
Publications (10 Years): 205

Top Venues

Publications

Shuang Qiu, Dake Zhang, Rui Yang, Boxiang Lyu, Tong Zhang
Traversing Pareto Optimal Policies: Provably Efficient Multi-Objective Reinforcement Learning. CoRR (2024)
Helbert Paat, Qing Lian, Weilong Yao, Tong Zhang
MEDL-U: Uncertainty-aware 3D Automatic Annotation based on Evidential Deep Learning. ICRA (2024)
Xunpeng Huang, Hanze Dong, Difan Zou, Tong Zhang
An Improved Analysis of Langevin Algorithms with Prior Diffusion for Non-Log-Concave Sampling. CoRR (2024)
Xunpeng Huang, Difan Zou, Hanze Dong, Yi Zhang, Yi-An Ma, Tong Zhang
Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference. CoRR (2024)
Rui Pan, Xiang Liu, Shizhe Diao, Renjie Pi, Jipeng Zhang, Chi Han, Tong Zhang
LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning. CoRR (2024)
Shizhe Diao, Pengcheng Wang, Yong Lin, Rui Pan, Xiang Liu, Tong Zhang
Active Prompting with Chain-of-Thought for Large Language Models. ACL (1) (2024)
Ying Su, Jipeng Zhang, Yangqiu Song, Tong Zhang
PipeNet: Question Answering with Semantic Pruning over Knowledge Graphs. *SEM@NAACL (2024)
Miao Lu, Han Zhong, Tong Zhang, Jose H. Blanchet
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm. CoRR (2024)
Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang
Towards Robust Offline Reinforcement Learning under Diverse Data Corruption. ICLR (2024)
Cheng Niu, Xingguang Wang, Xuxin Cheng, Juntong Song, Tong Zhang
Enhancing Dialogue State Tracking Models through LLM-backed User-Agents Simulation. ACL (1) (2024)
Haoxiang Wang, Wei Xiong, Tengyang Xie, Han Zhao, Tong Zhang
Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts. CoRR (2024)
Dake Zhang, Boxiang Lyu, Shuang Qiu, Mladen Kolar, Tong Zhang
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning. CoRR (2024)
Rui Xie, Asad Ul Haq, Linsen Ma, Krystal Sun, Sanchari Sen, Swagath Venkataramani, Liu Liu, Tong Zhang
SmartQuant: CXL-based AI Model Store in Support of Runtime Configurable Weight Quantization. CoRR (2024)
Rui Pan, Yuxing Liu, Xiaoyu Wang, Tong Zhang
Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise. ICLR (2024)
Rui Pan, Jipeng Zhang, Xingyuan Pan, Renjie Pi, Xiaoyu Wang, Tong Zhang
ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting. CoRR (2024)
Shixiang Chen, Shiqian Ma, Anthony Man-Cho So, Tong Zhang
Nonsmooth Optimization over the Stiefel Manifold and Beyond: Proximal Gradient Method and Recent Variants. SIAM Rev. 66 (2) (2024)
Ying Su, Tianqing Fang, Huiru Xiao, Weiqi Wang, Yangqiu Song, Tong Zhang, Lei Chen
EntailE: Introducing Textual Entailment in Commonsense Knowledge Graph Completion. CoRR (2024)
Renjie Pi, Tianyang Han, Wei Xiong, Jipeng Zhang, Runtao Liu, Rui Pan, Tong Zhang
Strengthening Multimodal Large Language Model with Bootstrapped Preference Optimization. CoRR (2024)
Hanning Zhang, Shizhe Diao, Yong Lin, Yi R. Fung, Qing Lian, Xingyao Wang, Yangyi Chen, Heng Ji, Tong Zhang
R-Tuning: Instructing Large Language Models to Say 'I Don't Know'. NAACL-HLT (2024)
Ruida Wang, Jipeng Zhang, Yizhen Jia, Rui Pan, Shizhe Diao, Renjie Pi, Tong Zhang
TheoremLlama: Transforming General-Purpose LLMs into Lean4 Experts. CoRR (2024)
Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang
Do CLIPs Always Generalize Better than ImageNet Models? CoRR (2024)
Yong Lin, Lu Tan, Yifan Hao, Honam Wong, Hanze Dong, Weizhong Zhang, Yujiu Yang, Tong Zhang
Spurious Feature Diversification Improves Out-of-distribution Generalization. ICLR (2024)
Zixuan Zhang, Revanth Gangi Reddy, Kevin Small, Tong Zhang, Heng Ji
Towards Better Generalization in Open-Domain Question Answering by Mitigating Context Memorization. CoRR (2024)
Cheng Niu, Yuanhao Wu, Juno Zhu, Siliang Xu, Kashun Shum, Randy Zhong, Juntong Song, Tong Zhang
RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models. ACL (1) (2024)
Yuxing Liu, Rui Pan, Tong Zhang
Large Batch Analysis for Adagrad Under Anisotropic Smoothness. CoRR (2024)
Xunpeng Huang, Hanze Dong, Yifan Hao, Yian Ma, Tong Zhang
Reverse Diffusion Monte Carlo. ICLR (2024)
Hanze Dong, Wei Xiong, Bo Pang, Haoxiang Wang, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang
RLHF Workflow: From Reward Modeling to Online RLHF. CoRR (2024)
Xunpeng Huang, Difan Zou, Yi-An Ma, Hanze Dong, Tong Zhang
Faster Sampling via Stochastic Gradient Proximal Sampler. CoRR (2024)
Rui Yang, Ruomeng Ding, Yong Lin, Huan Zhang, Tong Zhang
Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs. CoRR (2024)
Haoxiang Wang, Yong Lin, Wei Xiong, Rui Yang, Shizhe Diao, Shuang Qiu, Han Zhao, Tong Zhang
Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards. CoRR (2024)
Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang
On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data. Trans. Mach. Learn. Res. 2024 (2024)
Cheng Niu, Xingguang Wang, Xuxin Cheng, Juntong Song, Tong Zhang
Enhancing Dialogue State Tracking Models through LLM-backed User-Agents Simulation. CoRR (2024)
Shizhe Diao, Zhichao Huang, Ruijia Xu, Xuechun Li, Yong Lin, Xiao Zhou, Tong Zhang
Black-Box Prompt Learning for Pre-trained Language Models. Trans. Mach. Learn. Res. 2023 (2023)
Yong Lin, Lu Tan, Hangyu Lin, Zeming Zheng, Renjie Pi, Jipeng Zhang, Shizhe Diao, Haoxiang Wang, Han Zhao, Yuan Yao, Tong Zhang
Speciality vs Generality: An Empirical Study on Catastrophic Forgetting in Fine-tuning Foundation Models. CoRR (2023)
Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang
Posterior Sampling for Competitive RL: Function Approximation and Partial Observation. CoRR (2023)
Hanze Dong, Xi Wang, Yong Lin, Tong Zhang
Particle-based Variational Inference with Preconditioned Functional Gradient Flow. ICLR (2023)
Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang
Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game. 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)
Yong Lin, Chen Liu, Chenlu Ye, Qing Lian, Yuan Yao, Tong Zhang
Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning. CoRR (2023)
Shizhe Diao, Sedrick Scott Keh, Liangming Pan, Zhiliang Tian, Yan Song, Tong Zhang
Hashtag-Guided Low-Resource Tweet Classification. WWW (2023)
Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang
Towards Robust Offline Reinforcement Learning under Diverse Data Corruption. CoRR (2023)
Shizhe Diao, Pengcheng Wang, Yong Lin, Tong Zhang
Active Prompting with Chain-of-Thought for Large Language Models. CoRR (2023)
Shizhe Diao, Sedrick Scott Keh, Liangming Pan, Zhiliang Tian, Yan Song, Tong Zhang
Hashtag-Guided Low-Resource Tweet Classification. CoRR (2023)
Shizhe Diao, Rui Pan, Hanze Dong, Kashun Shum, Jipeng Zhang, Wei Xiong, Tong Zhang
LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. CoRR (2023)
Han Zhong, Tong Zhang
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes. NeurIPS (2023)
Alekh Agarwal, Yujia Jin, Tong Zhang
VOQL: Towards Optimal Regret in Model-free RL with Nonlinear Function Approximation. COLT (2023)
Kashun Shum, Shizhe Diao, Tong Zhang
Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data. CoRR (2023)
Rui Yang, Lin Yong, Xiaoteng Ma, Hao Hu, Chongjie Zhang, Tong Zhang
What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL? ICML (2023)
Hanze Dong, Wei Xiong, Deepanshu Goyal, Yihan Zhang, Winnie Chow, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, Tong Zhang
RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment. Trans. Mach. Learn. Res. 2023 (2023)
Helbert Paat, Qing Lian, Weilong Yao, Tong Zhang
MEDL-U: Uncertainty-aware 3D Automatic Annotator based on Evidential Deep Learning. CoRR (2023)
Jonathan Lee, Alekh Agarwal, Christoph Dann, Tong Zhang
Learning in POMDPs is Sample-Efficient with Hindsight Observability. ICML (2023)
Rui Pan, Shuo Xing, Shizhe Diao, Xiang Liu, Kashun Shum, Jipeng Zhang, Tong Zhang
Plum: Prompt Learning using Metaheuristic. CoRR (2023)
Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang
Weakly Supervised Disentangled Generative Causal Representation Learning. J. Mach. Learn. Res. 23 (2022)
Cong Fang, Yihong Gu, Weizhong Zhang, Tong Zhang
Convex Formulation of Overparameterized Deep Neural Networks. IEEE Trans. Inf. Theory 68 (8) (2022)
Tong Zhang
Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning. SIAM J. Math. Data Sci. 4 (2) (2022)
Yoav Freund, Yi-An Ma, Tong Zhang
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint. J. Mach. Learn. Res. 23 (2022)
Alekh Agarwal, Tong Zhang
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity. NeurIPS (2022)
Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions. CoRR (2022)
Ying Su, Zihao Wang, Tianqing Fang, Hongming Zhang, Yangqiu Song, Tong Zhang
MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge Representation. EMNLP (Findings) (2022)
Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning. CoRR (2022)
Rui Pan, Haishan Ye, Tong Zhang
Eigencurve: Optimal Learning Rate Schedule for SGD on Quadratic Objectives with Skewed Hessian Spectrums. ICLR (2022)
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu
A Field Guide to Federated Optimization. CoRR (2021)
Haishan Ye, Tong Zhang
DeEPCA: Decentralized Exact PCA with Linear Convergence Rate. J. Mach. Learn. Res. 22 (2021)
Xun Qian, Peter Richtárik, Tong Zhang
Error Compensated Distributed SGD Can Be Accelerated. NeurIPS (2021)
Rie Johnson, Tong Zhang
A Framework of Composite Functional Gradient Methods for Generative Adversarial Models. IEEE Trans. Pattern Anal. Mach. Intell. 43 (1) (2021)
Rui Pan, Haishan Ye, Tong Zhang
Eigencurve: Optimal Learning Rate Schedule for SGD on Quadratic Objectives with Skewed Hessian Spectrums. CoRR (2021)
Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning. NeurIPS (2021)
Cong Fang, Jason D. Lee, Pengkun Yang, Tong Zhang
Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks. COLT (2021)
Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
Finite-Sample Analysis for Decentralized Batch Multiagent Reinforcement Learning With Networked Agents. IEEE Trans. Autom. Control. 66 (12) (2021)
Shiwei Zhang, Wei Ke, Lin Yang, Qixiang Ye, Xiaopeng Hong, Yihong Gong, Tong Zhang
Discovery-and-Selection: Towards Optimal Multiple Instance Learning for Weakly Supervised Object Detection. CoRR (2021)
Haishan Ye, Tong Zhang
DeEPCA: Decentralized Exact PCA with Linear Convergence Rate. CoRR (2021)
Cong Fang, Hanze Dong, Tong Zhang
Mathematical Models of Overparameterized Neural Networks. Proc. IEEE 109 (5) (2021)
Jun Song, Yueyang Wang, Siliang Tang, Yin Zhang, Zhigang Chen, Zhongfei Zhang, Tong Zhang, Fei Wu
Local-Global Memory Neural Network for Medication Prediction. IEEE Trans. Neural Networks Learn. Syst. 32 (4) (2021)
Qi Chang, Zhennan Yan, Lohendran Baskaran, Hui Qu, Yikai Zhang, Tong Zhang, Shaoting Zhang, Dimitris N. Metaxas
Multi-modal AsynDGAN: Learn From Distributed Medical Image Data without Sharing Private Information. CoRR (2020)
Haishan Ye, Luo Luo, Ziang Zhou, Tong Zhang
Multi-consensus Decentralized Accelerated Gradient Descent. CoRR (2020)
Wenhan Luo, Peng Sun, Fangwei Zhong, Wei Liu, Tong Zhang, Yizhou Wang
End-to-End Active Object Tracking and Its Real-World Deployment via Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. 42 (6) (2020)
Shixiang Chen, Shiqian Ma, Anthony Man-Cho So, Tong Zhang
Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold. SIAM J. Optim. 30 (1) (2020)
Luo Luo, Haishan Ye, Zhichao Huang, Tong Zhang
Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems. NeurIPS (2020)
Rie Johnson, Tong Zhang
Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization. ICML (2020)
Luo Luo, Haishan Ye, Tong Zhang
Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems. CoRR (2020)
Qi Chang, Hui Qu, Yikai Zhang, Mert R. Sabuncu, Chao Chen, Tong Zhang, Dimitris N. Metaxas
Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data. CoRR (2020)
Zixiang Chen, Yuan Cao, Quanquan Gu, Tong Zhang
Mean-Field Analysis of Two-Layer Neural Networks: Non-Asymptotic Rates and Generalization Bounds. CoRR (2020)
Qi Chang, Hui Qu, Yikai Zhang, Mert R. Sabuncu, Chao Chen, Tong Zhang, Dimitris N. Metaxas
Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data. CVPR (2020)
Haishan Ye, Ziang Zhou, Luo Luo, Tong Zhang
Decentralized Accelerated Proximal Gradient Descent. NeurIPS (2020)
Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. CoRR (2020)
Chaoyang He, Haishan Ye, Li Shen, Tong Zhang
MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation. CVPR (2020)
Chaoyang He, Haishan Ye, Li Shen, Tong Zhang
MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation. CoRR (2020)
Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang
Disentangled Generative Causal Representation Learning. CoRR (2020)
Conghui Tan, Yuqiu Qian, Shiqian Ma, Tong Zhang
Accelerated dual-averaging primal-dual method for composite convex minimization. Optim. Methods Softw. 35 (4) (2020)
Baoyuan Wu, Li Shen, Tong Zhang, Bernard Ghanem
-Sphere Linear Program Reformulation. Int. J. Comput. Vis. 128 (7) (2020)
Haishan Ye, Wei Xiong, Tong Zhang
PMGT-VR: A decentralized proximal-gradient algorithmic framework with variance reduction. CoRR (2020)
Cong Fang, Jason D. Lee, Pengkun Yang, Tong Zhang
Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks. CoRR (2020)
Rie Johnson, Tong Zhang
Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization. CoRR (2020)
Yihong Gu, Weizhong Zhang, Cong Fang, Jason D. Lee, Tong Zhang
How to Characterize The Landscape of Overparameterized Convolutional Neural Networks. NeurIPS (2020)
Conghui Tan, Yuqiu Qian, Shiqian Ma, Tong Zhang
Accelerated Dual-Averaging Primal-Dual Method for Composite Convex Minimization. CoRR (2020)
Zhichao Huang, Tong Zhang
Black-Box Adversarial Attack with Transferable Model-based Embedding. ICLR (2020)
Cong Fang, Hanze Dong, Tong Zhang
Mathematical Models of Overparameterized Neural Networks. CoRR (2020)
Zixiang Chen, Yuan Cao, Quanquan Gu, Tong Zhang
A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks. NeurIPS (2020)
Zhichao Huang, Yaowei Huang, Tong Zhang
CorrAttack: Black-box Adversarial Attack with Structured Search. CoRR (2020)
Yinpeng Dong, Hang Su, Baoyuan Wu, Zhifeng Li, Wei Liu, Tong Zhang, Jun Zhu
Efficient Decision-based Black-box Adversarial Attacks on Face Recognition. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Tong Zhang