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ORCIDTong Zhang 0001
张潼
Person information
- unicode name: 张潼
- affiliation: Hong Kong University of Science and Technology, China
- affiliation (former): Tencent AI Lab, Shenzhen, China
- affiliation (former): Rutgers University, Department of Statistics, NJ, USA
- affiliation (former): Baidu Inc. Beijing, China
- affiliation (former): Yahoo
- affiliation (former): IBM T. J. Watson Research Center, Yorktown Heights, NY, USA
- affiliation (PhD): Stanford University, CA, USA
Other persons with the same name
- Tong Zhang — disambiguation page
- Tong Zhang 0002
![[0009-0009-8005-0043]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0009-0009-8005-0043")
— Rensselaer Polytechnic Institute, Troy, NY, USA (and 1 more) - Tong Zhang 0003 — Shanghai Jiaotong University, Department of Computer Science and Technology, China
- Tong Zhang 0004 — University of Southern California, Department of Electrical Engineering Systems, Los Angeles, CA, USA
- Tong Zhang 0005 — University of Illinois, Beckman Institute, Urbana, IL, USA
- Tong Zhang 0006 — SRA Corporation, Arlington, VA, USA
- Tong Zhang 0007 — Hewlett-Packard Labs, Palo Alto, CA, USA
- Tong Zhang 0008 — National University of Defense Technology, Changsha, China
- Tong Zhang 0009 — Wuhan University, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, China (and 2 more)
- Tong Zhang 0010 — Henan Polytechnic University, School of Mathematics and Information Science, Jiaozuo, China (and 1 more)
- Tong Zhang 0011 — Wuhan University of Technology, Intelligent Transportation Systems Research Center, China
- Tong Zhang 0012 — Tsinghua University, Department of Engineering Mechanics, School of Aerospace, Beijing, China
- Tong Zhang 0013 — Kyushu University, Graduate School of Information Science and Electrical Engineering, Fukuoka, Japan
- Tong Zhang 0014 — Southeast University, School of Electronic Science and Engineering, MOE Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Nanjing, China
- Tong Zhang 0015 — South China University of Technology, School of Electronics and Information, Guangzhou, China (and 1 more)
- Tong Zhang 0016 — Fuzhou University, College of Mathematics & Computer Science, China
- Tong Zhang 0017 — Peng Cheng Laboratory, Shenzhen, China (and 2 more)
- Tong Zhang 0018 — Tsinghua University, Department of Computer Science and Technology, TNList, Beijing, China
- Tong Zhang 0019 — University of Washington, Department of Electrical Engineering, Seattle, WA, USA
- Tong Zhang 0020 — University of Edinburgh, Institute for Digital Communications, Edinburgh, UK
- Tong Zhang 0021 — Nanjing University of Science and Technology, School of Computer Science and Technology, China (and 1 more)
- Tong Zhang 0023 — EPFL, Lausanne, Switzerland (and 1 more)
- Tong Zhang 0024 — Peking University, Institute of Computer Science and Technology, Beijing, China
- Tong Zhang 0025 — University of Windsor, ON, Canada
- Tong Zhang 0026 — Southern University of Science and Technology, Department of Electrical and Electronic Engineering, Shenzhen, China (and 1 more)
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2020 – today
- 2023
[j77]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)- [c202]Shizhe Diao, Tianyang Xu, Ruijia Xu, Jiawei Wang, Tong Zhang:
Mixture-of-Domain-Adapters: Decoupling and Injecting Domain Knowledge to Pre-trained Language Models' Memories. ACL (1) 2023: 5113-5129 - [c201]Xun Qian, Hanze Dong, Tong Zhang, Peter Richtárik:
Catalyst Acceleration of Error Compensated Methods Leads to Better Communication Complexity. AISTATS 2023: 615-649 - [c200]Alekh Agarwal, Yujia Jin, Tong Zhang:
VOQL: Towards Optimal Regret in Model-free RL with Nonlinear Function Approximation. COLT 2023: 987-1063 - [c199]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: 4977-5020 - [c198]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 - [c197]Hanze Dong, Xi Wang, Yong Lin, Tong Zhang:
Particle-based Variational Inference with Preconditioned Functional Gradient Flow. ICLR 2023 - [c196]Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang:
On the Convergence of Federated Averaging with Cyclic Client Participation. ICML 2023: 5677-5721 - [c195]Rudrajit Das, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi:
Beyond Uniform Lipschitz Condition in Differentially Private Optimization. ICML 2023: 7066-7101 - [c194]Jonathan Lee, Alekh Agarwal, Christoph Dann, Tong Zhang:
Learning in POMDPs is Sample-Efficient with Hindsight Observability. ICML 2023: 18733-18773 - [c193]Xiaoyu Wang, Mikael Johansson, Tong Zhang:
Generalized Polyak Step Size for First Order Optimization with Momentum. ICML 2023: 35836-35863 - [c192]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: 39543-39571 - [c191]Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang:
Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes. ICML 2023: 39834-39863 - [c190]Shizhe Diao, Sedrick Scott Keh, Liangming Pan, Zhiliang Tian, Yan Song, Tong Zhang:
Hashtag-Guided Low-Resource Tweet Classification. WWW 2023: 1415-1426 - [i173]Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang:
Model Agnostic Sample Reweighting for Out-of-Distribution Learning. CoRR abs/2301.09819 (2023) - [i172]Xiao Zhou, Renjie Pi, Weizhong Zhang, Yong Lin, Tong Zhang:
Probabilistic Bilevel Coreset Selection. CoRR abs/2301.09880 (2023) - [i171]Jonathan N. Lee, Alekh Agarwal, Christoph Dann, Tong Zhang:
Learning in POMDPs is Sample-Efficient with Hindsight Observability. CoRR abs/2301.13857 (2023) - [i170]Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang:
On the Convergence of Federated Averaging with Cyclic Client Participation. CoRR abs/2302.03109 (2023) - [i169]Shizhe Diao, Sedrick Scott Keh, Liangming Pan, Zhiliang Tian, Yan Song, Tong Zhang:
Hashtag-Guided Low-Resource Tweet Classification. CoRR abs/2302.10143 (2023) - [i168]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 abs/2302.10371 (2023) - [i167]Shizhe Diao, Pengcheng Wang, Yong Lin, Tong Zhang:
Active Prompting with Chain-of-Thought for Large Language Models. CoRR abs/2302.12246 (2023) - [i166]Kashun Shum, Shizhe Diao, Tong Zhang:
Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data. CoRR abs/2302.12822 (2023) - [i165]Shihong Ding, Hanze Dong, Cong Fang, Zhouchen Lin, Tong Zhang:
Provable Particle-based Primal-Dual Algorithm for Mixed Nash Equilibrium. CoRR abs/2303.00970 (2023) - [i164]Jianqing Fan, Cong Fang, Yihong Gu, Tong Zhang:
Environment Invariant Linear Least Squares. CoRR abs/2303.03092 (2023) - [i163]Hanze Dong, Wei Xiong, Deepanshu Goyal, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, Tong Zhang:
RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment. CoRR abs/2304.06767 (2023) - [i162]Han Zhong, Tong Zhang:
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes. CoRR abs/2305.08841 (2023) - [i161]Jose Blanchet, Miao Lu, Tong Zhang, Han Zhong:
Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage. CoRR abs/2305.09659 (2023) - [i160]Xiaoyu Wang, Rui Pan, Renjie Pi, Tong Zhang:
Effective Bilevel Optimization via Minimax Reformulation. CoRR abs/2305.13153 (2023) - [i159]Renjie Pi, Jiahui Gao, Shizhe Diao, Rui Pan, Hanze Dong, Jipeng Zhang, Lewei Yao, Jianhua Han, Hang Xu, Lingpeng Kong, Tong Zhang:
DetGPT: Detect What You Need via Reasoning. CoRR abs/2305.14167 (2023) - [i158]Rui Yang, Yong Lin, Xiaoteng Ma, Hao Hu, Chongjie Zhang, Tong Zhang:
What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL? CoRR abs/2305.18882 (2023) - [i157]Rie Johnson, Tong Zhang:
Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training. CoRR abs/2306.00169 (2023) - [i156]Shizhe Diao, Tianyang Xu, Ruijia Xu, Jiawei Wang, Tong Zhang:
Mixture-of-Domain-Adapters: Decoupling and Injecting Domain Knowledge to Pre-trained Language Models Memories. CoRR abs/2306.05406 (2023) - [i155]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 abs/2306.12420 (2023) - [i154]Xunpeng Huang, Hanze Dong, Yifan Hao, Yian Ma, Tong Zhang:
Monte Carlo Sampling without Isoperimetry: A Reverse Diffusion Approach. CoRR abs/2307.02037 (2023) - [i153]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 abs/2309.02476 (2023) - [i152]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 abs/2309.06256 (2023) - [i151]Helbert Paat, Qing Lian, Weilong Yao, Tong Zhang:
MEDL-U: Uncertainty-aware 3D Automatic Annotator based on Evidential Deep Learning. CoRR abs/2309.09599 (2023) - 2022
- [j76]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: 214:1-214:32 (2022) - [j75]Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang:
Weakly Supervised Disentangled Generative Causal Representation Learning. J. Mach. Learn. Res. 23: 241:1-241:55 (2022) - [j74]Minghan Yang, Andre Milzarek, Zaiwen Wen, Tong Zhang:
A stochastic extra-step quasi-Newton method for nonsmooth nonconvex optimization. Math. Program. 194(1): 257-303 (2022) - [j73]Cong Fang, Yihong Gu, Weizhong Zhang, Tong Zhang:
Convex Formulation of Overparameterized Deep Neural Networks. IEEE Trans. Inf. Theory 68(8): 5340-5352 (2022) - [c189]Ying Su, Hongming Zhang, Yangqiu Song, Tong Zhang:
Rare and Zero-shot Word Sense Disambiguation using Z-Reweighting. ACL (1) 2022: 4713-4723 - [c188]Ying Su, Hongming Zhang, Yangqiu Song, Tong Zhang:
Multilingual Word Sense Disambiguation with Unified Sense Representation. COLING 2022: 4193-4202 - [c187]Alekh Agarwal, Tong Zhang:
Minimax Regret Optimization for Robust Machine Learning under Distribution Shift. COLT 2022: 2704-2729 - [c186]Alekh Agarwal, Tong Zhang:
Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling. COLT 2022: 2776-2814 - [c185]Qing Lian, Botao Ye, Ruijia Xu, Weilong Yao, Tong Zhang:
Exploring Geometric Consistency for Monocular 3D Object Detection. CVPR 2022: 1675-1684 - [c184]Yong Lin, Hanze Dong, Hao Wang, Tong Zhang:
Bayesian Invariant Risk Minimization. CVPR 2022: 16000-16009 - [c183]Qing Lian, Yanbo Xu, Weilong Yao, Yingcong Chen, Tong Zhang:
Semi-supervised Monocular 3D Object Detection by Multi-view Consistency. ECCV (8) 2022: 715-731 - [c182]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: 1339-1351 - [c181]Ziniu Li, Yingru Li, Yushun Zhang, Tong Zhang, Zhi-Quan Luo:
HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning. ICLR 2022 - [c180]Rui Pan, Haishan Ye, Tong Zhang:
Eigencurve: Optimal Learning Rate Schedule for SGD on Quadratic Objectives with Skewed Hessian Spectrums. ICLR 2022 - [c179]Claudio Gentile, Zhilei Wang, Tong Zhang:
Achieving Minimax Rates in Pool-Based Batch Active Learning. ICML 2022: 7339-7367 - [c178]Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao:
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. ICML 2022: 13669-13703 - [c177]Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang:
A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games. ICML 2022: 24496-24523 - [c176]Renzhe Xu, Xingxuan Zhang, Zheyan Shen, Tong Zhang, Peng Cui:
A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization. ICML 2022: 24803-24829 - [c175]Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang:
Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. ICML 2022: 27117-27142 - [c174]Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang:
Model Agnostic Sample Reweighting for Out-of-Distribution Learning. ICML 2022: 27203-27221 - [c173]Xiao Zhou, Yong Lin, Weizhong Zhang, Tong Zhang:
Sparse Invariant Risk Minimization. ICML 2022: 27222-27244 - [c172]Xiao Zhou, Renjie Pi, Weizhong Zhang, Yong Lin, Zonghao Chen, Tong Zhang:
Probabilistic Bilevel Coreset Selection. ICML 2022: 27287-27302 - [c171]Alekh Agarwal, Tong Zhang:
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity. NeurIPS 2022 - [c170]Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu:
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions. NeurIPS 2022 - [i150]Shizhe Diao, Xuechun Li, Yong Lin, Zhichao Huang, Tong Zhang:
Black-box Prompt Learning for Pre-trained Language Models. CoRR abs/2201.08531 (2022) - [i149]Alekh Agarwal, Tong Zhang:
Minimax Regret Optimization for Robust Machine Learning under Distribution Shift. CoRR abs/2202.05436 (2022) - [i148]Claudio Gentile, Zhilei Wang, Tong Zhang:
Achieving Minimax Rates in Pool-Based Batch Active Learning. CoRR abs/2202.05448 (2022) - [i147]Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang:
Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. CoRR abs/2202.07511 (2022) - [i146]Alekh Agarwal, Tong Zhang:
Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling. CoRR abs/2203.08248 (2022) - [i145]Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu:
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions. CoRR abs/2205.06811 (2022) - [i144]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. CoRR abs/2205.15512 (2022) - [i143]Yi-An Ma, Teodor Vanislavov Marinov, Tong Zhang:
Dimension Independent Generalization of DP-SGD for Overparameterized Smooth Convex Optimization. CoRR abs/2206.01836 (2022) - [i142]Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao:
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. CoRR abs/2206.04569 (2022) - [i141]Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang:
On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data. CoRR abs/2206.04723 (2022) - [i140]Alekh Agarwal, Tong Zhang:
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity. CoRR abs/2206.07659 (2022) - [i139]Rudrajit Das, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi:
Beyond Uniform Lipschitz Condition in Differentially Private Optimization. CoRR abs/2206.10713 (2022) - [i138]Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert:
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning. CoRR abs/2208.10904 (2022) - [i137]Xinwei Shen, Kani Chen, Tong Zhang:
Asymptotic Statistical Analysis of f-divergence GAN. CoRR abs/2209.06853 (2022) - [i136]Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang:
A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games. CoRR abs/2210.01907 (2022) - [i135]Ying Su, Hongming Zhang, Yangqiu Song, Tong Zhang:
Multilingual Word Sense Disambiguation with Unified Sense Representation. CoRR abs/2210.07447 (2022) - [i134]Ying Su, Zihao Wang, Tianqing Fang, Hongming Zhang, Yangqiu Song, Tong Zhang:
MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge Representation. CoRR abs/2210.07570 (2022) - [i133]Han Zhong, Wei Xiong, Sirui Zheng, Liwei Wang, Zhaoran Wang, Zhuoran Yang, Tong Zhang:
GEC: A Unified Framework for Interactive Decision Making in MDP, POMDP, and Beyond. CoRR abs/2211.01962 (2022) - [i132]Hanze Dong, Shizhe Diao, Weizhong Zhang, Tong Zhang:
Normalizing Flow with Variational Latent Representation. CoRR abs/2211.11638 (2022) - [i131]Hanze Dong, Xi Wang, Yong Lin, Tong Zhang:
Particle-based Variational Inference with Preconditioned Functional Gradient Flow. CoRR abs/2211.13954 (2022) - [i130]Rui Pan, Shizhe Diao, Jianlin Chen, Tong Zhang:
ExtremeBERT: A Toolkit for Accelerating Pretraining of Customized BERT. CoRR abs/2211.17201 (2022) - [i129]Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang:
Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes. CoRR abs/2212.05949 (2022) - [i128]Alekh Agarwal, Yujia Jin, Tong Zhang:
VOQL: Towards Optimal Regret in Model-free RL with Nonlinear Function Approximation. CoRR abs/2212.06069 (2022) - 2021
- [j72]Haishan Ye, Tong Zhang:
DeEPCA: Decentralized Exact PCA with Linear Convergence Rate. J. Mach. Learn. Res. 22: 238:1-238:27 (2021) - [j71]Rie Johnson, Tong Zhang:
A Framework of Composite Functional Gradient Methods for Generative Adversarial Models. IEEE Trans. Pattern Anal. Mach. Intell. 43(1): 17-32 (2021) - [j70]Cong Fang, Hanze Dong, Tong Zhang:
Mathematical Models of Overparameterized Neural Networks. Proc. IEEE 109(5): 683-703 (2021) - [j69]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): 5925-5940 (2021) - [j68]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): 1723-1736 (2021) - [c169]Shizhe Diao, Ruijia Xu, Hongjin Su, Yilei Jiang, Yan Song, Tong Zhang:
Taming Pre-trained Language Models with N-gram Representations for Low-Resource Domain Adaptation. ACL/IJCNLP (1) 2021: 3336-3349 - [c168]Shizhe Diao, Xinwei Shen, Kashun Shum, Yan Song, Tong Zhang:
TILGAN: Transformer-based Implicit Latent GAN for Diverse and Coherent Text Generation. ACL/IJCNLP (Findings) 2021: 4844-4858 - [c167]Cong Fang, Jason D. Lee, Pengkun Yang, Tong Zhang:
Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks. COLT 2021: 1887-1936 - [c166]Zhichao Huang, Xintong Han, Jia Xu, Tong Zhang:
Few-Shot Human Motion Transfer by Personalized Geometry and Texture Modeling. CVPR 2021: 2297-2306 - [c165]Xiao Zhou, Weizhong Zhang, Hang Xu, Tong Zhang:
Effective Sparsification of Neural Networks With Global Sparsity Constraint. CVPR 2021: 3599-3608 - [c164]Yawen Duan, Xin Chen, Hang Xu, Zewei Chen, Xiaodan Liang, Tong Zhang, Zhenguo Li:
TransNAS-Bench-101: Improving Transferability and Generalizability of Cross-Task Neural Architecture Search. CVPR 2021: 5251-5260 - [c163]Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang:
Joint-DetNAS: Upgrade Your Detector With NAS, Pruning and Dynamic Distillation. CVPR 2021: 10175-10184 - [c162]Duo Li, Jie Hu, Changhu Wang, Xiangtai Li, Qi She, Lei Zhu, Tong Zhang, Qifeng Chen:
Involution: Inverting the Inherence of Convolution for Visual Recognition. CVPR 2021: 12321-12330 - [c161]Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang:
G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation. ICCV 2021: 3571-3580 - [c160]Yuhui Ding, Quanming Yao, Huan Zhao, Tong Zhang:
DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks. KDD 2021: 279-288 - [c159]Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert:
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning. NeurIPS 2021: 12040-12051 - [c158]Xiao Zhou, Weizhong Zhang, Zonghao Chen, Shizhe Diao, Tong Zhang:
Efficient Neural Network Training via Forward and Backward Propagation Sparsification. NeurIPS 2021: 15216-15229 - [c157]Xun Qian, Peter Richtárik, Tong Zhang:
Error Compensated Distributed SGD Can Be Accelerated. NeurIPS 2021: 30401-30413 - [e2]Marina Meila, Tong Zhang:
Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event. Proceedings of Machine Learning Research 139, PMLR 2021 [contents] - [i127]Haishan Ye, Tong Zhang:
DeEPCA: Decentralized Exact PCA with Linear Convergence Rate. CoRR abs/2102.03990 (2021) - [i126]Duo Li, Jie Hu, Changhu Wang, Xiangtai Li, Qi She, Lei Zhu, Tong Zhang, Qifeng Chen:
Involution: Inverting the Inherence of Convolution for Visual Recognition. CoRR abs/2103.06255 (2021) - [i125]Zhichao Huang, Xintong Han, Jia Xu, Tong Zhang:
Few-Shot Human Motion Transfer by Personalized Geometry and Texture Modeling. CoRR abs/2103.14338 (2021) - [i124]Qing Lian, Botao Ye, Ruijia Xu, Weilong Yao, Tong Zhang:
Geometry-aware data augmentation for monocular 3D object detection. CoRR abs/2104.05858 (2021) - [i123]Yan Song, Tong Zhang, Yonggang Wang, Kai-Fu Lee:
ZEN 2.0: Continue Training and Adaption for N-gram Enhanced Text Encoders. CoRR abs/2105.01279 (2021) - [i122]Xiao Zhou, Weizhong Zhang, Hang Xu, Tong Zhang:
Effective Sparsification of Neural Networks with Global Sparsity Constraint. CoRR abs/2105.01571 (2021) - [i121]Yawen Duan, Xin Chen, Hang Xu, Zewei Chen, Xiaodan Liang, Tong Zhang, Zhenguo Li:
TransNAS-Bench-101: Improving Transferability and Generalizability of Cross-Task Neural Architecture Search. CoRR abs/2105.11871 (2021) - [i120]Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang:
Joint-DetNAS: Upgrade Your Detector with NAS, Pruning and Dynamic Distillation. CoRR abs/2105.12971 (2021) - [i119]Hanting Chen, Yunhe Wang, Chang Xu, Chao Xu, Chunjing Xu, Tong Zhang:
Adder Neural Networks. CoRR abs/2105.14202 (2021) - [i118]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 Horváth, 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 abs/2107.06917 (2021) - [i117]Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang:
G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation. CoRR abs/2108.07482 (2021) - [i116]