Zhang, Tong

309 publications

NeurIPS 2025 ASGO: Adaptive Structured Gradient Optimization Kang An, Yuxing Liu, Rui Pan, Yi Ren, Shiqian Ma, Donald Goldfarb, Tong Zhang

ICLR 2025 AdaGrad Under Anisotropic Smoothness Yuxing Liu, Rui Pan, Tong Zhang

TMLR 2025 Adaptive Multi-Step Refinement Network for Robust Point Cloud Registration Zhi Chen, Yufan Ren, Tong Zhang, Zheng Dang, Wenbing Tao, Sabine Susstrunk, Mathieu Salzmann

ICLRW 2025 An Property-Prompted Multi-Scale Data Augmentation Approach for Crystal Representation Zhongyi Deng, Shuzhou Li, Tong Zhang, C. L. Philip Chen

ICLR 2025 Building Math Agents with Multi-Turn Iterative Preference Learning Wei Xiong, Chengshuai Shi, Jiaming Shen, Aviv Rosenberg, Zhen Qin, Daniele Calandriello, Misha Khalman, Rishabh Joshi, Bilal Piot, Mohammad Saleh, Chi Jin, Tong Zhang, Tianqi Liu

ICML 2025 Catoni Contextual Bandits Are Robust to Heavy-Tailed Rewards Chenlu Ye, Yujia Jin, Alekh Agarwal, Tong Zhang

IJCAI 2025 DFMU: Distribution-Based Framework for Modeling Aleatoric Uncertainty in Multimodal Sentiment Analysis Chen Tang, Tingrui Shen, Xinrong Gong, Chong Zhao, Tong Zhang

ICML 2025 Demystifying Singular Defects in Large Language Models Haoqi Wang, Tong Zhang, Mathieu Salzmann

CVPR 2025 Distribution Prototype Diffusion Learning for Open-Set Supervised Anomaly Detection Fuyun Wang, Tong Zhang, Yuanzhi Wang, Yide Qiu, Xin Liu, Xu Guo, Zhen Cui

ICML 2025 EmbodiedBench: Comprehensive Benchmarking Multi-Modal Large Language Models for Vision-Driven Embodied Agents Rui Yang, Hanyang Chen, Junyu Zhang, Mark Zhao, Cheng Qian, Kangrui Wang, Qineng Wang, Teja Venkat Koripella, Marziyeh Movahedi, Manling Li, Heng Ji, Huan Zhang, Tong Zhang

TMLR 2025 Entropy-Regularized Process Reward Model Hanning Zhang, Pengcheng Wang, Shizhe Diao, Yong Lin, Rui Pan, Hanze Dong, Dylan Zhang, Pavlo Molchanov, Tong Zhang

CVPR 2025 FDS: Frequency-Aware Denoising Score for Text-Guided Latent Diffusion Image Editing Yufan Ren, Zicong Jiang, Tong Zhang, Søren Forchhammer, Sabine Süsstrunk

NeurIPS 2025 GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents Qianhui Wu, Kanzhi Cheng, Rui Yang, Chaoyun Zhang, Jianwei Yang, Huiqiang Jiang, Jian Mu, Baolin Peng, Bo Qiao, Reuben Tan, Si Qin, Lars Liden, Qingwei Lin, Huan Zhang, Tong Zhang, Jianbing Zhang, Dongmei Zhang, Jianfeng Gao

CVPR 2025 Generating Multimodal Driving Scenes via Next-Scene Prediction Yanhao Wu, Haoyang Zhang, Tianwei Lin, Lichao Huang, Shujie Luo, Rui Wu, Congpei Qiu, Wei Ke, Tong Zhang

IJCAI 2025 Going Beyond Consistency: Target-Oriented Multi-View Graph Neural Network Sujia Huang, Lele Fu, Shuman Zhuang, Yide Qiu, Bo Huang, Zhen Cui, Tong Zhang

CoRL 2025 HuB: Learning Extreme Humanoid Balance Tong Zhang, Boyuan Zheng, Ruiqian Nai, Yingdong Hu, Yen-Jen Wang, Geng Chen, Fanqi Lin, Jiongye Li, Chuye Hong, Koushil Sreenath, Yang Gao

TMLR 2025 Localize-and-Stitch: Efficient Model Merging via Sparse Task Arithmetic Yifei He, Yuzheng Hu, Yong Lin, Tong Zhang, Han Zhao

ICML 2025 Logarithmic Regret for Online KL-Regularized Reinforcement Learning Heyang Zhao, Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang

ICML 2025 MA-LoT: Model-Collaboration Lean-Based Long Chain-of-Thought Reasoning Enhances Formal Theorem Proving Ruida Wang, Rui Pan, Yuxin Li, Jipeng Zhang, Yizhen Jia, Shizhe Diao, Renjie Pi, Junjie Hu, Tong Zhang

ICCV 2025 MatchDiffusion: Training-Free Generation of Match-Cuts Alejandro Pardo, Fabio Pizzati, Tong Zhang, Alexander Pondaven, Philip Torr, Juan Camilo Perez, Bernard Ghanem

NeurIPS 2025 MergeBench: A Benchmark for Merging Domain-Specialized LLMs Yifei He, Siqi Zeng, Yuzheng Hu, Rui Yang, Tong Zhang, Han Zhao

NeurIPS 2025 One for All: Universal Topological Primitive Transfer for Graph Structure Learning Yide Qiu, Tong Zhang, Xing Cai, Hui Yan, Zhen Cui

JMLR 2025 Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning Yong Lin, Chen Liu, Chenlu Ye, Qing Lian, Yuan Yao, Tong Zhang

NeurIPS 2025 Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL Jiarui Yao, Yifan Hao, Hanning Zhang, Hanze Dong, Wei Xiong, Nan Jiang, Tong Zhang

ICLR 2025 Personalized Visual Instruction Tuning Renjie Pi, Jianshu Zhang, Tianyang Han, Jipeng Zhang, Rui Pan, Tong Zhang

ICLR 2025 PivotMesh: Generic 3D Mesh Generation via Pivot Vertices Guidance Haohan Weng, Yikai Wang, Tong Zhang, C. L. Philip Chen, Jun Zhu

ICLR 2025 Refining CLIP's Spatial Awareness: A Visual-Centric Perspective Congpei Qiu, Yanhao Wu, Wei Ke, Xiuxiu Bai, Tong Zhang

ICLR 2025 Rotated Runtime Smooth: Training-Free Activation Smoother for Accurate INT4 Inference Ke Yi, Zengke Liu, Jianwei Zhang, Chengyuan Li, Tong Zhang, Junyang Lin, Jingren Zhou

TMLR 2025 SEE-DPO: Self Entropy Enhanced Direct Preference Optimization Shivanshu Shekhar, Shreyas Singh, Tong Zhang

CVPR 2025 Scaling Mesh Generation via Compressive Tokenization Haohan Weng, Zibo Zhao, Biwen Lei, Xianghui Yang, Jian Liu, Zeqiang Lai, Zhuo Chen, Yuhong Liu, Jie Jiang, Chunchao Guo, Tong Zhang, Shenghua Gao, C.L. Philip Chen

AAAI 2025 Scene Graph-Grounded Image Generation Fuyun Wang, Tong Zhang, Yuanzhi Wang, Xiaoya Zhang, Xin Liu, Zhen Cui

ICCV 2025 Self-Ensembling Gaussian Splatting for Few-Shot Novel View Synthesis Chen Zhao, Xuan Wang, Tong Zhang, Saqib Javed, Mathieu Salzmann

NeurIPS 2025 Sharp Analysis for KL-Regularized Contextual Bandits and RLHF Heyang Zhao, Chenlu Ye, Quanquan Gu, Tong Zhang

NeurIPS 2025 Thinking vs. Doing: Improving Agent Reasoning by Scaling Test-Time Interaction Junhong Shen, Hao Bai, Lunjun Zhang, Yifei Zhou, Amrith Setlur, Shengbang Tong, Diego Caples, Nan Jiang, Tong Zhang, Ameet Talwalkar, Aviral Kumar

ICCV 2025 TimeBooth: Disentangled Facial Invariant Representation for Diverse and Personalized Face Aging Zepeng Su, Zhulin Liu, Zongyan Zhang, Tong Zhang, C.L.Philip Chen

ICML 2025 Understanding Overadaptation in Supervised Fine-Tuning: The Role of Ensemble Methods Yifan Hao, Xingyuan Pan, Hanning Zhang, Chenlu Ye, Rui Pan, Tong Zhang

NeurIPS 2025 UniHG: A Large-Scale Universal Heterogeneous Graph Dataset and Benchmark for Representation Learning and Cross-Domain Transferring Yide Qiu, Tong Zhang, Shaoxiang Ling, Xing Cai, Ziqi Gu, Zhen Cui

NeurIPS 2025 Value Diffusion Reinforcement Learning Xiaoliang Hu, Fuyun Wang, Tong Zhang, Zhen Cui

ICLR 2024 3D-Aware Hypothesis & Verification for Generalizable Relative Object Pose Estimation Chen Zhao, Tong Zhang, Mathieu Salzmann

NeurIPS 2024 A Sober Look at the Robustness of CLIPs to Spurious Features Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang

ICLR 2024 A Unique M-Pattern for Micro-Expression Spotting in Long Videos Jinxuan Wang, Shiting Xu, Tong Zhang

ICLR 2024 Accelerated Convergence of Stochastic Heavy Ball Method Under Anisotropic Gradient Noise Rui Pan, Yuxing Liu, Xiaoyu Wang, Tong Zhang

NeurIPS 2024 AdanCA: Neural Cellular Automata as Adaptors for More Robust Vision Transformer Yitao Xu, Tong Zhang, Sabine Süsstrunk

ECCV 2024 An Incremental Unified Framework for Small Defect Inspection Jiaqi Tang, Hao Lu, Xiaogang Xu, Ruizheng Wu, Sixing Hu, Tong Zhang, Tsz Wa Cheng, Ming Ge, Ying-Cong Chen, Fugee Tsung

WACV 2024 CVTHead: One-Shot Controllable Head Avatar with Vertex-Feature Transformer Haoyu Ma, Tong Zhang, Shanlin Sun, Xiangyi Yan, Kun Han, Xiaohui Xie

TMLR 2024 Controlling the Fidelity and Diversity of Deep Generative Models via Pseudo Density Shuangqi Li, Chen Liu, Tong Zhang, Hieu Le, Sabine Susstrunk, Mathieu Salzmann

TMLR 2024 DSI2I: Dense Style for Unpaired Exemplar-Based Image-to- Image Translation Baran Ozaydin, Tong Zhang, Sabine Susstrunk, Mathieu Salzmann

CVPR 2024 DVMNet: Computing Relative Pose for Unseen Objects Beyond Hypotheses Chen Zhao, Tong Zhang, Zheng Dang, Mathieu Salzmann

ECCV 2024 Data Augmentation via Latent Diffusion for Saliency Prediction Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang, Mathieu Salzmann, Sabine Süsstrunk

CVPR 2024 Desigen: A Pipeline for Controllable Design Template Generation Haohan Weng, Danqing Huang, Yu Qiao, Zheng Hu, Chin-Yew Lin, Tong Zhang, C. L. Philip Chen

ICMLW 2024 Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm Miao Lu, Han Zhong, Tong Zhang, Jose Blanchet

NeurIPS 2024 Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms Miao Lu, Han Zhong, Tong Zhang, Jose Blanchet

JMLR 2024 Fast Rates in Pool-Based Batch Active Learning Claudio Gentile, Zhilei Wang, Tong Zhang

COLT 2024 Faster Sampling Without Isoperimetry via Diffusion-Based Monte Carlo Xunpeng Huang, Difan Zou, Hanze Dong, Yi-An Ma, Tong Zhang

ICML 2024 Faster Sampling via Stochastic Gradient Proximal Sampler Xunpeng Huang, Difan Zou, Hanze Dong, Yian Ma, Tong Zhang

CoRL 2024 General Flow as Foundation Affordance for Scalable Robot Learning Chengbo Yuan, Chuan Wen, Tong Zhang, Yang Gao

NeurIPS 2024 Image Textualization: An Automatic Framework for Generating Rich and Detailed Image Descriptions Renjie Pi, Jianshu Zhang, Jipeng Zhang, Rui Pan, Zhekai Chen, Tong Zhang

CVPR 2024 InNeRF360: Text-Guided 3D-Consistent Object Inpainting on 360-Degree Neural Radiance Fields Dongqing Wang, Tong Zhang, Alaa Abboud, Sabine Süsstrunk

ICML 2024 Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF Under KL-Constraint Wei Xiong, Hanze Dong, Chenlu Ye, Ziqi Wang, Han Zhong, Heng Ji, Nan Jiang, Tong Zhang

NeurIPS 2024 LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning Rui Pan, Xiang Liu, Shizhe Diao, Renjie Pi, Jipeng Zhang, Chi Han, Tong Zhang

CoRL 2024 Leveraging Locality to Boost Sample Efficiency in Robotic Manipulation Tong Zhang, Yingdong Hu, Jiacheng You, Yang Gao

ICLR 2024 Mind Your Augmentation: The Key to Decoupling Dense Self-Supervised Learning Congpei Qiu, Tong Zhang, Yanhao Wu, Wei Ke, Mathieu Salzmann, Sabine Süsstrunk

CVPR 2024 Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning Through Object Exchange Yanhao Wu, Tong Zhang, Wei Ke, Congpei Qiu, Sabine Süsstrunk, Mathieu Salzmann

JMLR 2024 On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu, Zhichao Huang, Mathieu Salzmann, Tong Zhang, Sabine Süsstrunk

TMLR 2024 On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang

NeurIPS 2024 Online Iterative Reinforcement Learning from Human Feedback with General Preference Model Chenlu Ye, Wei Xiong, Yuheng Zhang, Hanze Dong, Nan Jiang, Tong Zhang

JMLR 2024 PAPAL: A Provable PArticle-Based Primal-Dual ALgorithm for Mixed Nash Equilibrium Shihong Ding, Hanze Dong, Cong Fang, Zhouchen Lin, Tong Zhang

CVPR 2024 PerceptionGPT: Effectively Fusing Visual Perception into LLM Renjie Pi, Lewei Yao, Jiahui Gao, Jipeng Zhang, Tong Zhang

ICML 2024 Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning Dake Zhang, Boxiang Lyu, Shuang Qiu, Mladen Kolar, Tong Zhang

TMLR 2024 RLHF Workflow: From Reward Modeling to Online RLHF Hanze Dong, Wei Xiong, Bo Pang, Haoxiang Wang, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang

NeurIPS 2024 Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs Rui Yang, Ruomeng Ding, Yong Lin, Huan Zhang, Tong Zhang

CoRL 2024 Reinforcement Learning with Foundation Priors: Let Embodied Agent Efficiently Learn on Its Own Weirui Ye, Yunsheng Zhang, Haoyang Weng, Xianfan Gu, Shengjie Wang, Tong Zhang, Mengchen Wang, Pieter Abbeel, Yang Gao

ICLR 2024 Reverse Diffusion Monte Carlo Xunpeng Huang, Hanze Dong, Yifan Hao, Yian Ma, Tong Zhang

NeurIPS 2024 Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference Xunpeng Huang, Difan Zou, Hanze Dong, Yi Zhang, Yian Ma, Tong Zhang

ICMLW 2024 Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference Xunpeng Huang, Difan Zou, Hanze Dong, Yi Zhang, Yian Ma, Tong Zhang

ECCV 2024 SINDER: Repairing the Singular Defects of DINOv2 Haoqi Wang, Tong Zhang, Mathieu Salzmann

NeurIPSW 2024 Sharp Analysis for KL-Regularized Contextual Bandits and RLHF Heyang Zhao, Chenlu Ye, Quanquan Gu, Tong Zhang

ICLR 2024 Spurious Feature Diversification Improves Out-of-Distribution Generalization Lin Yong, Lu Tan, Yifan Hao, Ho Nam Wong, Hanze Dong, Weizhong Zhang, Yujiu Yang, Tong Zhang

ECCV 2024 Strengthening Multimodal Large Language Model with Bootstrapped Preference Optimization Renjie Pi, Tianyang Han, Wei Xiong, Jipeng Zhang, Runtao Liu, Rui Pan, Tong Zhang

AAAI 2024 TagFog: Textual Anchor Guidance and Fake Outlier Generation for Visual Out-of-Distribution Detection Jiankang Chen, Tong Zhang, Wei-Shi Zheng, Ruixuan Wang

ICML 2024 The Non-Linear $f$-Design and Applications to Interactive Learning Alekh Agarwal, Jian Qian, Alexander Rakhlin, Tong Zhang

ICML 2024 Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption Chenlu Ye, Jiafan He, Quanquan Gu, Tong Zhang

ICLR 2024 Towards Robust Offline Reinforcement Learning Under Diverse Data Corruption Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang

ECCVW 2024 Unlocking Comics: The AI4VA Dataset for Visual Understanding Peter Grönquist, Deblina Bhattacharjee, Bahar Aydemir, Baran Ozaydin, Tong Zhang, Mathieu Salzmann, Sabine Süsstrunk

NeurIPS 2023 A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes Han Zhong, Tong Zhang

CoRL 2023 A Universal Semantic-Geometric Representation for Robotic Manipulation Tong Zhang, Yingdong Hu, Hanchen Cui, Hang Zhao, Yang Gao

ICML 2023 Beyond Uniform Lipschitz Condition in Differentially Private Optimization Rudrajit Das, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi

TMLR 2023 Black-Box Prompt Learning for Pre-Trained Language Models Shizhe Diao, Zhichao Huang, Ruijia Xu, Xuechun Li, Lin Yong, Xiao Zhou, Tong Zhang

AISTATS 2023 Catalyst Acceleration of Error Compensated Methods Leads to Better Communication Complexity Xun Qian, Hanze Dong, Tong Zhang, Peter Richtarik

ICML 2023 Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang

NeurIPS 2023 Corruption-Robust Offline Reinforcement Learning with General Function Approximation Chenlu Ye, Rui Yang, Quanquan Gu, Tong Zhang

AAAI 2023 Covariate-Shift Generalization via Random Sample Weighting Yue He, Xinwei Shen, Renzhe Xu, Tong Zhang, Yong Jiang, Wenchao Zou, Peng Cui

AAAI 2023 Deep Graph Structural Infomax Wenting Zhao, Gongping Xu, Zhen Cui, Siqiang Luo, Cheng Long, Tong Zhang

ICCVW 2023 Diff3DHPE: A Diffusion Model for 3D Human Pose Estimation Jieming Zhou, Tong Zhang, Zeeshan Hayder, Lars Petersson, Mehrtash Harandi

NeurIPS 2023 Double Pessimism Is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage Jose Blanchet, Miao Lu, Tong Zhang, Han Zhong

NeurIPS 2023 Double Randomized Underdamped Langevin with Dimension-Independent Convergence Guarantee Yuanshi Liu, Cong Fang, Tong Zhang

CVPR 2023 DyNCA: Real-Time Dynamic Texture Synthesis Using Neural Cellular Automata Ehsan Pajouheshgar, Yitao Xu, Tong Zhang, Sabine Süsstrunk

ICML 2023 Generalized Polyak Step Size for First Order Optimization with Momentum Xiaoyu Wang, Mikael Johansson, Tong Zhang

NeurIPS 2023 Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training Rie Johnson, Tong Zhang

IJCAI 2023 Learn and Sample Together: Collaborative Generation for Graphic Design Layout Haohan Weng, Danqing Huang, Tong Zhang, Chin-Yew Lin

ICML 2023 Learning in POMDPs Is Sample-Efficient with Hindsight Observability Jonathan Lee, Alekh Agarwal, Christoph Dann, Tong Zhang

JMLR 2023 Multi-Consensus Decentralized Accelerated Gradient Descent Haishan Ye, Luo Luo, Ziang Zhou, Tong Zhang

ICCV 2023 NEMTO: Neural Environment Matting for Novel View and Relighting Synthesis of Transparent Objects Dongqing Wang, Tong Zhang, Sabine Süsstrunk

ICLR 2023 Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang

ICML 2023 On the Convergence of Federated Averaging with Cyclic Client Participation Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang

ICLR 2023 Particle-Based Variational Inference with Preconditioned Functional Gradient Flow Hanze Dong, Xi Wang, Lin Yong, Tong Zhang

NeurIPS 2023 Posterior Sampling for Competitive RL: Function Approximation and Partial Observation Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang

TMLR 2023 RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment Hanze Dong, Wei Xiong, Deepanshu Goyal, Yihan Zhang, Winnie Chow, Rui Pan, Shizhe Diao, Jipeng Zhang, KaShun Shum, Tong Zhang

CVPR 2023 Spatiotemporal Self-Supervised Learning for Point Clouds in the Wild Yanhao Wu, Tong Zhang, Wei Ke, Sabine Süsstrunk, Mathieu Salzmann

CVPR 2023 TempSAL - Uncovering Temporal Information for Deep Saliency Prediction Bahar Aydemir, Ludo Hoffstetter, Tong Zhang, Mathieu Salzmann, Sabine Süsstrunk

COLT 2023 VO$Q$L: Towards Optimal Regret in Model-Free RL with Nonlinear Function Approximation Alekh Agarwal, Yujia Jin, Tong Zhang

COLT 2023 Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu

CVPR 2023 VolRecon: Volume Rendering of Signed Ray Distance Functions for Generalizable Multi-View Reconstruction Yufan Ren, Fangjinhua Wang, Tong Zhang, Marc Pollefeys, Sabine Süsstrunk

ICML 2023 What Is Essential for Unseen Goal Generalization of Offline Goal-Conditioned RL? Rui Yang, Lin Yong, Xiaoteng Ma, Hao Hu, Chongjie Zhang, Tong Zhang

NeurIPSW 2022 A Neural Tangent Kernel Perspective on Function-Space Regularization in Neural Networks Zonghao Chen, Xupeng Shi, Tim G. J. Rudner, Qixuan Feng, Weizhong Zhang, Tong Zhang

ICML 2022 A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang

ICLRW 2022 A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang

ICML 2022 A Theoretical Analysis on Independence-Driven Importance Weighting for Covariate-Shift Generalization Renzhe Xu, Xingxuan Zhang, Zheyan Shen, Tong Zhang, Peng Cui

ICML 2022 Achieving Minimax Rates in Pool-Based Batch Active Learning Claudio Gentile, Zhilei Wang, Tong Zhang

CVPR 2022 Bayesian Invariant Risk Minimization Yong Lin, Hanze Dong, Hao Wang, Tong Zhang

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 Eigencurve: Optimal Learning Rate Schedule for SGD on Quadratic Objectives with Skewed Hessian Spectrums Rui Pan, Haishan Ye, Tong Zhang

CVPR 2022 Exploring Geometric Consistency for Monocular 3D Object Detection Qing Lian, Botao Ye, Ruijia Xu, Weilong Yao, Tong Zhang

AAAI 2022 Frequency-Aware Contrastive Learning for Neural Machine Translation Tong Zhang, Wei Ye, Baosong Yang, Long Zhang, Xingzhang Ren, Dayiheng Liu, Jinan Sun, Shikun Zhang, Haibo Zhang, Wen Zhao

ICLR 2022 HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning Ziniu Li, Yingru Li, Yushun Zhang, Tong Zhang, Zhi-Quan Luo

CVPR 2022 Leverage Your Local and Global Representations: A New Self-Supervised Learning Strategy Tong Zhang, Congpei Qiu, Wei Ke, Sabine Süsstrunk, Mathieu Salzmann

COLT 2022 Minimax Regret Optimization for Robust Machine Learning Under Distribution Shift Alekh Agarwal, Tong Zhang

ICML 2022 Model Agnostic Sample Reweighting for Out-of-Distribution Learning Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang

NeurIPS 2022 Model-Based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal, Tong Zhang

TMLR 2022 Modeling Object Dissimilarity for Deep Saliency Prediction Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang, Seungryong Kim, Mathieu Salzmann, Sabine Süsstrunk

CVPR 2022 MulT: An End-to-End Multitask Learning Transformer Deblina Bhattacharjee, Tong Zhang, Sabine Süsstrunk, Mathieu Salzmann

NeurIPS 2022 Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu

COLT 2022 Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-Efficiency of Posterior Sampling Alekh Agarwal, Tong Zhang

NeurIPSW 2022 Particle-Based Variational Inference with Preconditioned Functional Gradient Flow Hanze Dong, Xi Wang, Lin Yong, Tong Zhang

ICML 2022 Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang

ICLRW 2022 Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang

ICML 2022 Probabilistic Bilevel Coreset Selection Xiao Zhou, Renjie Pi, Weizhong Zhang, Yong Lin, Zonghao Chen, Tong Zhang

ECCV 2022 RC-MVSNet: Unsupervised Multi-View Stereo with Neural Rendering Di Chang, Aljaž Božič, Tong Zhang, Qingsong Yan, Yingcong Chen, Sabine Süsstrunk, Matthias Nießner

ECCV 2022 Semi-Supervised Monocular 3D Object Detection by Multi-View Consistency Qing Lian, Yanbo Xu, Weilong Yao, Yingcong Chen, Tong Zhang

ICML 2022 Sparse Invariant Risk Minimization Xiao Zhou, Yong Lin, Weizhong Zhang, Tong Zhang

JMLR 2022 Weakly Supervised Disentangled Generative Causal Representation Learning Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang

JMLR 2022 When Is the Convergence Time of Langevin Algorithms Dimension Independent? a Composite Optimization Viewpoint Yoav Freund, Yi-An Ma, Tong Zhang

NeurIPS 2021 A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert

JMLR 2021 DeEPCA: Decentralized Exact PCA with Linear Convergence Rate Haishan Ye, Tong Zhang

AAAI 2021 Deep Wasserstein Graph Discriminant Learning for Graph Classification Tong Zhang, Yun Wang, Zhen Cui, Chuanwei Zhou, Baoliang Cui, Haikuan Huang, Jian Yang

CVPR 2021 Effective Sparsification of Neural Networks with Global Sparsity Constraint Xiao Zhou, Weizhong Zhang, Hang Xu, Tong Zhang

NeurIPS 2021 Efficient Neural Network Training via Forward and Backward Propagation Sparsification Xiao Zhou, Weizhong Zhang, Zonghao Chen, Shizhe Diao, Tong Zhang

NeurIPS 2021 Error Compensated Distributed SGD Can Be Accelerated Xun Qian, Peter Richtarik, Tong Zhang

CVPR 2021 Few-Shot Human Motion Transfer by Personalized Geometry and Texture Modeling Zhichao Huang, Xintong Han, Jia Xu, Tong Zhang

ICCV 2021 G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-Guided Feature Imitation Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang

IJCAI 2021 Graph Deformer Network Wenting Zhao, Yuan Fang, Zhen Cui, Tong Zhang, Jian Yang

AAAI 2021 Graph Game Embedding Xiaobin Hong, Tong Zhang, Zhen Cui, Yuge Huang, Pengcheng Shen, Shaoxin Li, Jian Yang

CVPR 2021 Involution: Inverting the Inherence of Convolution for Visual Recognition Duo Li, Jie Hu, Changhu Wang, Xiangtai Li, Qi She, Lei Zhu, Tong Zhang, Qifeng Chen

CVPR 2021 Joint-DetNAS: Upgrade Your Detector with NAS, Pruning and Dynamic Distillation Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang

COLT 2021 Modeling from Features: A Mean-Field Framework for Over-Parameterized Deep Neural Networks Cong Fang, Jason Lee, Pengkun Yang, Tong Zhang

CVPR 2021 Reinforced Attention for Few-Shot Learning and Beyond Jie Hong, Pengfei Fang, Weihao Li, Tong Zhang, Christian Simon, Mehrtash Harandi, Lars Petersson

CVPR 2021 TransNAS-Bench-101: Improving Transferability and Generalizability of Cross-Task Neural Architecture Search Yawen Duan, Xin Chen, Hang Xu, Zewei Chen, Xiaodan Liang, Tong Zhang, Zhenguo Li

CVPR 2021 Uncertainty-Aware Joint Salient Object and Camouflaged Object Detection Aixuan Li, Jing Zhang, Yunqiu Lv, Bowen Liu, Tong Zhang, Yuchao Dai

ICCV 2021 Wasserstein Coupled Graph Learning for Cross-Modal Retrieval Yun Wang, Tong Zhang, Xueya Zhang, Zhen Cui, Yuge Huang, Pengcheng Shen, Shaoxin Li, Jian Yang

NeurIPS 2020 A Generalized Neural Tangent Kernel Analysis for Two-Layer Neural Networks Zixiang Chen, Yuan Cao, Quanquan Gu, Tong Zhang

ICLR 2020 Black-Box Adversarial Attack with Transferable Model-Based Embedding Zhichao Huang, Tong Zhang

NeurIPS 2020 Bridging the Gap Between Sample-Based and One-Shot Neural Architecture Search with BONAS Han Shi, Renjie Pi, Hang Xu, Zhenguo Li, James T. Kwok, Tong Zhang

ECCV 2020 CATCH: Context-Based Meta Reinforcement Learning for Transferrable Architecture Search Xin Chen, Yawen Duan, Zewei Chen, Hang Xu, Zihao Chen, Xiaodan Liang, Tong Zhang, Zhenguo Li

NeurIPS 2020 Decentralized Accelerated Proximal Gradient Descent Haishan Ye, Ziang Zhou, Luo Luo, Tong Zhang

ICLR 2020 Graph Inference Learning for Semi-Supervised Classification Chunyan Xu, Zhen Cui, Xiaobin Hong, Tong Zhang, Jian Yang, Wei Liu

ECCV 2020 Graph Wasserstein Correlation Analysis for Movie Retrieval Xueya Zhang, Tong Zhang, Xiaobin Hong, Zhen Cui, Jian Yang

ICML 2020 Guided Learning of Nonconvex Models Through Successive Functional Gradient Optimization Rie Johnson, Tong Zhang

NeurIPS 2020 How to Characterize the Landscape of Overparameterized Convolutional Neural Networks Yihong Gu, Weizhong Zhang, Cong Fang, Jason Lee, Tong Zhang

NeurIPS 2020 Model Rubik’s Cube: Twisting Resolution, Depth and Width for TinyNets Kai Han, Yunhe Wang, Qiulin Zhang, Wei Zhang, Chunjing Xu, Tong Zhang

AAAI 2020 Optimal Feature Transport for Cross-View Image Geo-Localization Yujiao Shi, Xin Yu, Liu Liu, Tong Zhang, Hongdong Li

NeurIPS 2020 Residual Distillation: Towards Portable Deep Neural Networks Without Shortcuts Guilin Li, Junlei Zhang, Yunhe Wang, Chuanjian Liu, Matthias Tan, Yunfeng Lin, Wei Zhang, Jiashi Feng, Tong Zhang

AAAI 2020 Stable Learning via Sample Reweighting Zheyan Shen, Peng Cui, Tong Zhang, Kun Kuang

NeurIPS 2020 Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems Luo Luo, Haishan Ye, Zhichao Huang, Tong Zhang

AAAI 2020 Variational Pathway Reasoning for EEG Emotion Recognition Tong Zhang, Zhen Cui, Chunyan Xu, Wenming Zheng, Jian Yang

ICLR 2019 DHER: Hindsight Experience Replay for Dynamic Goals Meng Fang, Cheng Zhou, Bei Shi, Boqing Gong, Jia Xu, Tong Zhang

NeurIPS 2019 Divergence-Augmented Policy Optimization Qing Wang, Yingru Li, Jiechao Xiong, Tong Zhang

ICML 2019 DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression Hanlin Tang, Chen Yu, Xiangru Lian, Tong Zhang, Ji Liu

AAAI 2019 Dynamic Layer Aggregation for Neural Machine Translation with Routing-by-Agreement Zi-Yi Dou, Zhaopeng Tu, Xing Wang, Longyue Wang, Shuming Shi, Tong Zhang

ICML 2019 Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI Lei Han, Peng Sun, Yali Du, Jiechao Xiong, Qing Wang, Xinghai Sun, Han Liu, Tong Zhang

JMLR 2019 Layer-Wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models Kean Ming Tan, Junwei Lu, Tong Zhang, Han Liu

CVPRW 2019 Learning Object-Wise Semantic Representation for Detection in Remote Sensing Imagery Chengzheng Li, Chunyan Xu, Zhen Cui, Dan Wang, Zequn Jie, Tong Zhang, Jian Yang

ICML 2019 NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks Yandong Li, Lijun Li, Liqiang Wang, Tong Zhang, Boqing Gong

ICML 2019 Neural Collaborative Subspace Clustering Tong Zhang, Pan Ji, Mehrtash Harandi, Wenbing Huang, Hongdong Li

AAAI 2019 Neural Machine Translation with Adequacy-Oriented Learning Xiang Kong, Zhaopeng Tu, Shuming Shi, Eduard H. Hovy, Tong Zhang

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

JMLR 2019 Robust Frequent Directions with Application in Online Learning Luo Luo, Cheng Chen, Zhihua Zhang, Wu-Jun Li, Tong Zhang

COLT 2019 Sharp Analysis for Nonconvex SGD Escaping from Saddle Points Cong Fang, Zhouchen Lin, Tong Zhang

JMLR 2019 Utilizing Second Order Information in Minibatch Stochastic Variance Reduced Proximal Iterations Jialei Wang, Tong Zhang

IJCAI 2018 A Novel Neural Network Model Based on Cerebral Hemispheric Asymmetry for EEG Emotion Recognition Yang Li, Wenming Zheng, Zhen Cui, Tong Zhang, Yuan Zong

NeurIPS 2018 Adaptive Sampling Towards Fast Graph Representation Learning Wenbing Huang, Tong Zhang, Yu Rong, Junzhou Huang

ICML 2018 An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method Li Shen, Peng Sun, Yitong Wang, Wei Liu, Tong Zhang

ICML 2018 Candidates vs. Noises Estimation for Large Multi-Class Classification Problem Lei Han, Yiheng Huang, Tong Zhang

NeurIPS 2018 Communication Compression for Decentralized Training Hanlin Tang, Shaoduo Gan, Ce Zhang, Tong Zhang, Ji Liu

ICML 2018 Composite Functional Gradient Learning of Generative Adversarial Models Rie Johnson, Tong Zhang

ICML 2018 End-to-End Active Object Tracking via Reinforcement Learning Wenhan Luo, Peng Sun, Fangwei Zhong, Wei Liu, Tong Zhang, Yizhou Wang

ICML 2018 Error Compensated Quantized SGD and Its Applications to Large-Scale Distributed Optimization Jiaxiang Wu, Weidong Huang, Junzhou Huang, Tong Zhang

NeurIPS 2018 Exponentially Weighted Imitation Learning for Batched Historical Data Qing Wang, Jiechao Xiong, Lei Han, Peng Sun, Han Liu, Tong Zhang

ICML 2018 Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar

NeurIPS 2018 Gradient Sparsification for Communication-Efficient Distributed Optimization Jianqiao Wangni, Jialei Wang, Ji Liu, Tong Zhang

ICML 2018 Graphical Nonconvex Optimization via an Adaptive Convex Relaxation Qiang Sun, Kean Ming Tan, Han Liu, Tong Zhang

ECCV 2018 Modeling Varying Camera-IMU Time Offset in Optimization-Based Visual-Inertial Odometry Yonggen Ling, Linchao Bao, Zequn Jie, Fengming Zhu, Ziyang Li, Shanmin Tang, Yongsheng Liu, Wei Liu, Tong Zhang

ECCV 2018 Neural Stereoscopic Image Style Transfer Xinyu Gong, Haozhi Huang, Lin Ma, Fumin Shen, Wei Liu, Tong Zhang

ECCV 2018 Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition Yitong Wang, Dihong Gong, Zheng Zhou, Xing Ji, Hao Wang, Zhifeng Li, Wei Liu, Tong Zhang

ECCV 2018 Recurrent Fusion Network for Image Captioning Wenhao Jiang, Lin Ma, Yu-Gang Jiang, Wei Liu, Tong Zhang

NeurIPS 2018 SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator Cong Fang, Chris Junchi Li, Zhouchen Lin, Tong Zhang

ICML 2018 Safe Element Screening for Submodular Function Minimization Weizhong Zhang, Bin Hong, Lin Ma, Wei Liu, Tong Zhang

NeurIPS 2018 Stochastic Expectation Maximization with Variance Reduction Jianfei Chen, Jun Zhu, Yee Whye Teh, Tong Zhang

NeurIPS 2018 Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity Conghui Tan, Tong Zhang, Shiqian Ma, Ji Liu

ECCV 2018 Super-Identity Convolutional Neural Network for Face Hallucination Kaipeng Zhang, Zhanpeng Zhang, Chia-Wen Cheng, Winston H. Hsu, Yu Qiao, Wei Liu, Tong Zhang

AAAI 2018 Translating Pro-Drop Languages with Reconstruction Models Longyue Wang, Zhaopeng Tu, Shuming Shi, Tong Zhang, Yvette Graham, Qun Liu

ECCV 2018 Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks Minjun Li, Haozhi Huang, Lin Ma, Wei Liu, Tong Zhang, Yugang Jiang

ECCV 2018 Video Re-Localization Yang Feng, Lin Ma, Wei Liu, Tong Zhang, Jiebo Luo

JMLR 2017 A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization Shun Zheng, Jialei Wang, Fen Xia, Wei Xu, Tong Zhang

NeurIPS 2017 Deep Subspace Clustering Networks Pan Ji, Tong Zhang, Hongdong Li, Mathieu Salzmann, Ian Reid

NeurIPS 2017 Diffusion Approximations for Online Principal Component Estimation and Global Convergence Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang

ICML 2017 Efficient Distributed Learning with Sparsity Jialei Wang, Mladen Kolar, Nathan Srebro, Tong Zhang

NeurIPS 2017 Efficient Optimization for Linear Dynamical Systems with Applications to Clustering and Sparse Coding Wenbing Huang, Mehrtash Harandi, Tong Zhang, Lijie Fan, Fuchun Sun, Junzhou Huang

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 Projection-Free Distributed Online Learning in Networks Wenpeng Zhang, Peilin Zhao, Wenwu Zhu, Steven C. H. Hoi, Tong Zhang

NeurIPS 2016 Exact Recovery of Hard Thresholding Pursuit Xiaotong Yuan, Ping Li, Tong Zhang

NeurIPS 2016 Learning Additive Exponential Family Graphical Models via $\ell_{2,1}$-Norm Regularized M-Estimation Xiaotong Yuan, Ping Li, Tong Zhang, Qingshan Liu, Guangcan Liu

ICML 2016 Sparse Nonlinear Regression: Parameter Estimation Under Nonconvexity Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina Eldar, Tong Zhang

ICML 2016 Supervised and Semi-Supervised Text Categorization Using LSTM for Region Embeddings Rie Johnson, Tong Zhang

JMLR 2016 Towards More Efficient SPSD Matrix Approximation and CUR Matrix Decomposition Shusen Wang, Zhihua Zhang, Tong Zhang

ICML 2015 Adaptive Stochastic Alternating Direction Method of Multipliers Peilin Zhao, Jinwei Yang, Tong Zhang, Ping Li

JMLR 2015 Learning Sparse Low-Threshold Linear Classifiers Sivan Sabato, Shai Shalev-Shwartz, Nathan Srebro, Daniel Hsu, Tong Zhang

NeurIPS 2015 Local Smoothness in Variance Reduced Optimization Daniel Vainsencher, Han Liu, Tong Zhang

IJCAI 2015 Matrix Factorization with Scale-Invariant Parameters Guangxiang Zeng, Hengshu Zhu, Qi Liu, Ping Luo, Enhong Chen, Tong Zhang

NeurIPS 2015 Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling Zheng Qu, Peter Richtarik, Tong Zhang

NeurIPS 2015 Semi-Supervised Convolutional Neural Networks for Text Categorization via Region Embedding Rie Johnson, Tong Zhang

ICML 2015 Stochastic Optimization with Importance Sampling for Regularized Loss Minimization Peilin Zhao, Tong Zhang

ICML 2014 A Convergence Rate Analysis for LogitBoost, MART and Their Variant Peng Sun, Tong Zhang, Jie Zhou

ICML 2014 Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization Shai Shalev-Shwartz, Tong Zhang

UAI 2014 Batch-Mode Active Learning via Error Bound Minimization Quanquan Gu, Tong Zhang, Jiawei Han

ICML 2014 Communication-Efficient Distributed Optimization Using an Approximate Newton-Type Method Ohad Shamir, Nati Srebro, Tong Zhang

COLT 2014 Compressed Counting Meets Compressed Sensing Ping Li, Cun-Hui Zhang, Tong Zhang

ICML 2014 Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization Xiaotong Yuan, Ping Li, Tong Zhang

NeurIPS 2013 Accelerated Mini-Batch Stochastic Dual Coordinate Ascent Shai Shalev-Shwartz, Tong Zhang

NeurIPS 2013 Accelerating Stochastic Gradient Descent Using Predictive Variance Reduction Rie Johnson, Tong Zhang

UAI 2013 High-Dimensional Joint Sparsity Random Effects Model for Multi-Task Learning Krishnakumar Balasubramanian, Kai Yu, Tong Zhang

JMLR 2013 Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization Shai Shalev-Shwartz, Tong Zhang

ICML 2013 Stochastic Gradient Descent for Non-Smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir, Tong Zhang

JMLR 2013 Truncated Power Method for Sparse Eigenvalue Problems Xiao-Tong Yuan, Tong Zhang

ICML 2012 A Proximal-Gradient Homotopy Method for the L1-Regularized Least-Squares Problem Lin Xiao, Tong Zhang

COLT 2012 Random Design Analysis of Ridge Regression Daniel Hsu, Sham M. Kakade, Tong Zhang

NeurIPS 2012 Selective Labeling via Error Bound Minimization Quanquan Gu, Tong Zhang, Jiawei Han, Chris H. Ding

UAI 2011 Efficient Optimal Learning for Contextual Bandits Miroslav Dudík, Daniel J. Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang

NeurIPS 2011 Greedy Model Averaging Dong Dai, Tong Zhang

NeurIPS 2011 Learning to Search Efficiently in High Dimensions Zhen Li, Huazhong Ning, Liangliang Cao, Tong Zhang, Yihong Gong, Thomas S. Huang

JMLR 2011 Learning with Structured Sparsity Junzhou Huang, Tong Zhang, Dimitris Metaxas

NeurIPS 2011 Spectral Methods for Learning Multivariate Latent Tree Structure Animashree Anandkumar, Kamalika Chaudhuri, Daniel J. Hsu, Sham M. Kakade, Le Song, Tong Zhang

NeurIPS 2010 Agnostic Active Learning Without Constraints Alina Beygelzimer, Daniel J. Hsu, John Langford, Tong Zhang

JMLR 2010 Analysis of Multi-Stage Convex Relaxation for Sparse Regularization Tong Zhang

NeurIPS 2010 Deep Coding Network Yuanqing Lin, Tong Zhang, Shenghuo Zhu, Kai Yu

ECCV 2010 Image Classification Using Super-Vector Coding of Local Image Descriptors Xi Zhou, Kai Yu, Tong Zhang, Thomas S. Huang

ICML 2010 Improved Local Coordinate Coding Using Local Tangents Kai Yu, Tong Zhang

COLT 2009 A Spectral Algorithm for Learning Hidden Markov Models Daniel J. Hsu, Sham M. Kakade, Tong Zhang

ICML 2009 Learning Nonlinear Dynamic Models John Langford, Ruslan Salakhutdinov, Tong Zhang

ICML 2009 Learning with Structured Sparsity Junzhou Huang, Tong Zhang, Dimitris N. Metaxas

NeurIPS 2009 Multi-Label Prediction via Compressed Sensing Daniel J. Hsu, Sham M. Kakade, John Langford, Tong Zhang

NeurIPS 2009 Nonlinear Learning Using Local Coordinate Coding Kai Yu, Tong Zhang, Yihong Gong

JMLR 2009 On the Consistency of Feature Selection Using Greedy Least Squares Regression Tong Zhang

JMLR 2009 Sparse Online Learning via Truncated Gradient John Langford, Lihong Li, Tong Zhang

COLT 2008 21st Annual Conference on Learning Theory - COLT 2008, Helsinki, Finland, July 9-12, 2008 Rocco A. Servedio, Tong Zhang

NeurIPS 2008 Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models Tong Zhang

NeurIPS 2008 Multi-Stage Convex Relaxation for Learning with Sparse Regularization Tong Zhang

NeurIPS 2008 Sparse Online Learning via Truncated Gradient John Langford, Lihong Li, Tong Zhang

NeurIPS 2007 A General Boosting Method and Its Application to Learning Ranking Functions for Web Search Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier Chapelle, Keke Chen, Gordon Sun

COLT 2007 Margin Based Active Learning Maria-Florina Balcan, Andrei Z. Broder, Tong Zhang

JMLR 2007 On the Effectiveness of Laplacian Normalization for Graph Semi-Supervised Learning Rie Johnson, Tong Zhang

NeurIPS 2007 The Epoch-Greedy Algorithm for Multi-Armed Bandits with Side Information John Langford, Tong Zhang

ICML 2007 Two-View Feature Generation Model for Semi-Supervised Learning Rie Kubota Ando, Tong Zhang

NeurIPS 2006 Learning on Graph with Laplacian Regularization Rie K. Ando, Tong Zhang

COLT 2006 Subset Ranking Using Regression David Cossock, Tong Zhang

JMLR 2005 A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data Rie Kubota Ando, Tong Zhang

NeurIPS 2005 Analysis of Spectral Kernel Design Based Semi-Supervised Learning Tong Zhang, Rie Kubota Ando

CVPR 2005 Audio-Visual Affect Recognition Through Multi-Stream Fused HMM for HCI Zhihong Zeng, Jilin Tu, Brian Pianfetti, Ming Liu, Tong Zhang, ZhenQiu Zhang, Thomas S. Huang, Stephen E. Levinson

COLT 2005 Data Dependent Concentration Bounds for Sequential Prediction Algorithms Tong Zhang

COLT 2005 Localized Upper and Lower Bounds for Some Estimation Problems Tong Zhang

NeurIPS 2004 Class-Size Independent Generalization Analsysis of Some Discriminative Multi-Category Classification Tong Zhang

COLT 2004 On the Convergence of MDL Density Estimation Tong Zhang

ICML 2004 Solving Large Scale Linear Prediction Problems Using Stochastic Gradient Descent Algorithms Tong Zhang

JMLR 2004 Statistical Analysis of Some Multi-Category Large Margin Classification Methods Tong Zhang

NeurIPS 2004 Support Vector Classification with Input Data Uncertainty Jinbo Bi, Tong Zhang

NeurIPS 2003 An Infinity-Sample Theory for Multi-Category Large Margin Classification Tong Zhang

JMLR 2003 Generalization Error Bounds for Bayesian Mixture Algorithms Ron Meir, Tong Zhang

JMLR 2003 Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity Shie Mannor, Ron Meir, Tong Zhang

NeurIPS 2003 Learning Bounds for a Generalized Family of Bayesian Posterior Distributions Tong Zhang

NeCo 2003 Leave-One-Out Bounds for Kernel Methods Tong Zhang

ICML 2003 On the Convergence of Boosting Procedures Tong Zhang, Bin Yu

NeCo 2002 Approximation Bounds for Some Sparse Kernel Regression Algorithms Tong Zhang

JMLR 2002 Covering Number Bounds of Certain Regularized Linear Function Classes Tong Zhang

NeurIPS 2002 Data-Dependent Bounds for Bayesian Mixture Methods Ron Meir, Tong Zhang

NeurIPS 2002 Effective Dimension and Generalization of Kernel Learning Tong Zhang

MLJ 2002 On the Dual Formulation of Regularized Linear Systems with Convex Risks Tong Zhang

JMLR 2002 Recommender Systems Using Linear Classifiers Tong Zhang, Vijay S. Iyengar

ICML 2002 Statistical Behavior and Consistency of Support Vector Machines, Boosting, and Beyond Tong Zhang

JMLR 2002 Text Chunking Based on a Generalization of Winnow Tong Zhang, Fred Damerau, David Johnson

COLT 2002 The Consistency of Greedy Algorithms for Classification Shie Mannor, Ron Meir, Tong Zhang

COLT 2001 A Leave-One-Out Cross Validation Bound for Kernel Methods with Applications in Learning Tong Zhang

COLT 2001 A Sequential Approximation Bound for Some Sample-Dependent Convex Optimization Problems with Applications in Learning Tong Zhang

ICML 2001 Some Sparse Approximation Bounds for Regression Problems Tong Zhang

NeurIPS 2000 Convergence of Large Margin Separable Linear Classification Tong Zhang

NeurIPS 2000 Regularized Winnow Methods Tong Zhang

CVPR 1999 Fast, Robust, and Consistent Camera Motion Estimation Tong Zhang, Carlo Tomasi

NeurIPS 1999 Some Theoretical Results Concerning the Convergence of Compositions of Regularized Linear Functions Tong Zhang

COLT 1999 Theoretical Analysis of a Class of Randomized Regularization Methods Tong Zhang

ECCV 1996 Optimal Surface Smoothing as Filter Design Gabriel Taubin, Tong Zhang, Gene H. Golub