Jin, Rong

189 publications

ICML 2025 MM-RLHF: The Next Step Forward in Multimodal LLM Alignment Yifan Zhang, Tao Yu, Haochen Tian, Chaoyou Fu, Peiyan Li, Jianshu Zeng, Wulin Xie, Yang Shi, Huanyu Zhang, Junkang Wu, Xue Wang, Yibo Hu, Bin Wen, Tingting Gao, Zhang Zhang, Fan Yang, Di Zhang, Liang Wang, Rong Jin

ICLR 2025 MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios That Are Difficult for Humans? YiFan Zhang, Huanyu Zhang, Haochen Tian, Chaoyou Fu, Shuangqing Zhang, Junfei Wu, Feng Li, Kun Wang, Qingsong Wen, Zhang Zhang, Liang Wang, Rong Jin

ICLR 2024 CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting Xue Wang, Tian Zhou, Qingsong Wen, Jinyang Gao, Bolin Ding, Rong Jin

CVPR 2024 Structured Model Probing: Empowering Efficient Transfer Learning by Structured Regularization Zhi-Fan Wu, Chaojie Mao, Wue Wang, Jianwen Jiang, Yiliang Lv, Rong Jin

ICML 2023 AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation Yifan Zhang, Xue Wang, Kexin Jin, Kun Yuan, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan

TMLR 2023 Attentional-Biased Stochastic Gradient Descent Qi Qi, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang

CVPR 2023 Beyond Appearance: A Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks Weihua Chen, Xianzhe Xu, Jian Jia, Hao Luo, Yaohua Wang, Fan Wang, Rong Jin, Xiuyu Sun

ICML 2023 FeDXL: Provable Federated Learning for Deep X-Risk Optimization Zhishuai Guo, Rong Jin, Jiebo Luo, Tianbao Yang

ICLR 2023 Free Lunch for Domain Adversarial Training: Environment Label Smoothing YiFan Zhang, Xue Wang, Jian Liang, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan

CVPR 2023 Making Vision Transformers Efficient from a Token Sparsification View Shuning Chang, Pichao Wang, Ming Lin, Fan Wang, David Junhao Zhang, Rong Jin, Mike Zheng Shou

NeurIPS 2023 One Fits All: Power General Time Series Analysis by Pretrained LM Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, Rong Jin

NeurIPS 2023 OneNet: Enhancing Time Series Forecasting Models Under Concept Drift by Online Ensembling Yifan Zhang, Qingsong Wen, Xue Wang, Weiqi Chen, Liang Sun, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan

CVPR 2023 Progressive Backdoor Erasing via Connecting Backdoor and Adversarial Attacks Bingxu Mu, Zhenxing Niu, Le Wang, Xue Wang, Qiguang Miao, Rong Jin, Gang Hua

AAAI 2022 A Trend-Driven Fashion Design System for Rapid Response Marketing in E-Commerce Lianghua Huang, Yu Liu, Bin Wang, Pan Pan, Rong Jin

NeurIPSW 2022 An Empirical Study on Distribution Shift Robustness from the Perspective of Pre-Training and Data Augmentation Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Rong Jin, Xiangyang Ji, Antoni B. Chan

ICLR 2022 CDTrans: Cross-Domain Transformer for Unsupervised Domain Adaptation Tongkun Xu, Weihua Chen, Pichao Wang, Fan Wang, Hao Li, Rong Jin

CVPR 2022 CHEX: CHannel EXploration for CNN Model Compression Zejiang Hou, Minghai Qin, Fei Sun, Xiaolong Ma, Kun Yuan, Yi Xu, Yen-Kuang Chen, Rong Jin, Yuan Xie, Sun-Yuan Kung

CVPR 2022 Decoupling and Recoupling Spatiotemporal Representation for RGB-D-Based Motion Recognition Benjia Zhou, Pichao Wang, Jun Wan, Yanyan Liang, Fan Wang, Du Zhang, Zhen Lei, Hao Li, Rong Jin

ICLR 2022 Effective Model Sparsification by Scheduled Grow-and-Prune Methods Xiaolong Ma, Minghai Qin, Fei Sun, Zejiang Hou, Kun Yuan, Yi Xu, Yanzhi Wang, Yen-Kuang Chen, Rong Jin, Yuan Xie

ICLR 2022 Entroformer: A Transformer-Based Entropy Model for Learned Image Compression Yichen Qian, Xiuyu Sun, Ming Lin, Zhiyu Tan, Rong Jin

ICML 2022 FEDformer: Frequency Enhanced Decomposed Transformer for Long-Term Series Forecasting Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, Rong Jin

NeurIPS 2022 FiLM: Frequency Improved Legendre Memory Model for Long-Term Time Series Forecasting Tian Zhou, Ziqing Ma, Xue Wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin

NeurIPSW 2022 GLINKX: A Scalable Unified Framework for Homophilous and Heterophilous Graphs Marios Papachristou, Rishab Goel, Frank Portman, Matthew Miller, Rong Jin

NeurIPS 2022 Grow and Merge: A Unified Framework for Continuous Categories Discovery Xinwei Zhang, Jianwen Jiang, Yutong Feng, Zhi-Fan Wu, Xibin Zhao, Hai Wan, Mingqian Tang, Rong Jin, Yue Gao

CVPR 2022 Hybrid Relation Guided Set Matching for Few-Shot Action Recognition Xiang Wang, Shiwei Zhang, Zhiwu Qing, Mingqian Tang, Zhengrong Zuo, Changxin Gao, Rong Jin, Nong Sang

NeurIPS 2022 Improved Fine-Tuning by Better Leveraging Pre-Training Data Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Xiangyang Ji, Antoni B. Chan, Rong Jin

ECCV 2022 KVT: k-NN Attention for Boosting Vision Transformers Pichao Wang, Xue Wang, Fan Wang, Ming Lin, Shuning Chang, Hao Li, Rong Jin

CVPR 2022 Learning from Untrimmed Videos: Self-Supervised Video Representation Learning with Hierarchical Consistency Zhiwu Qing, Shiwei Zhang, Ziyuan Huang, Yi Xu, Xiang Wang, Mingqian Tang, Changxin Gao, Rong Jin, Nong Sang

ICML 2022 MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection Zhenhong Sun, Ming Lin, Xiuyu Sun, Zhiyu Tan, Hao Li, Rong Jin

ICLR 2022 Rethinking Supervised Pre-Training for Better Downstream Transferring Yutong Feng, Jianwen Jiang, Mingqian Tang, Rong Jin, Yue Gao

NeurIPS 2022 Robust Graph Structure Learning via Multiple Statistical Tests Yaohua Wang, Fangyi Zhang, Ming Lin, Senzhang Wang, Xiuyu Sun, Rong Jin

AAAI 2022 Scaled ReLU Matters for Training Vision Transformers Pichao Wang, Xue Wang, Hao Luo, Jingkai Zhou, Zhipeng Zhou, Fan Wang, Hao Li, Rong Jin

NeurIPS 2022 Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks Yunwen Lei, Rong Jin, Yiming Ying

ECCV 2022 TransFGU: A Top-Down Approach to Fine-Grained Unsupervised Semantic Segmentation Zhaoyuan Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li, Rong Jin

CVPR 2022 Unsupervised Visual Representation Learning by Online Constrained K-Means Qi Qian, Yuanhong Xu, Juhua Hu, Hao Li, Rong Jin

NeurIPS 2021 An Online Method for a Class of Distributionally Robust Optimization with Non-Convex Objectives Qi Qi, Zhishuai Guo, Yi Xu, Rong Jin, Tianbao Yang

CVPR 2021 Communication Efficient SGD via Gradient Sampling with Bayes Prior Liuyihan Song, Kang Zhao, Pan Pan, Yu Liu, Yingya Zhang, Yinghui Xu, Rong Jin

ICML 2021 Dash: Semi-Supervised Learning with Dynamic Thresholding Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yu-Feng Li, Baigui Sun, Hao Li, Rong Jin

ICLR 2021 Learning Accurate Entropy Model with Global Reference for Image Compression Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li, Zhenhong Sun, Li Hao, Rong Jin

CVPR 2021 Learning Position and Target Consistency for Memory-Based Video Object Segmentation Li Hu, Peng Zhang, Bang Zhang, Pan Pan, Yinghui Xu, Rong Jin

CVPR 2021 Self-Supervised Motion Learning from Static Images Ziyuan Huang, Shiwei Zhang, Jianwen Jiang, Mingqian Tang, Rong Jin, Marcelo H. Ang

CVPR 2021 Self-Supervised Video Representation Learning by Context and Motion Decoupling Lianghua Huang, Yu Liu, Bin Wang, Pan Pan, Yinghui Xu, Rong Jin

AAAI 2021 Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning Yu Liu, Lianghua Huang, Pan Pan, Bin Wang, Yinghui Xu, Rong Jin

ICCV 2021 Weakly Supervised Representation Learning with Coarse Labels Yuanhong Xu, Qi Qian, Hao Li, Rong Jin, Juhua Hu

ICCV 2021 Zen-NAS: A Zero-Shot NAS for High-Performance Image Recognition Ming Lin, Pichao Wang, Zhenhong Sun, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin

MLJ 2020 High-Dimensional Model Recovery from Random Sketched Data by Exploring Intrinsic Sparsity Tianbao Yang, Lijun Zhang, Qihang Lin, Shenghuo Zhu, Rong Jin

IJCAI 2019 A Practical Semi-Parametric Contextual Bandit Yi Peng, Miao Xie, Jiahao Liu, Xuying Meng, Nan Li, Cheng Yang, Tao Yao, Rong Jin

MLJ 2019 A Simple Homotopy Proximal Mapping Algorithm for Compressive Sensing Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou

UAI 2019 Learning with Non-Convex Truncated Losses by SGD Yi Xu, Shenghuo Zhu, Sen Yang, Chi Zhang, Rong Jin, Tianbao Yang

ICCVW 2019 MuffNet: Multi-Layer Feature Federation for Mobile Deep Learning Hesen Chen, Ming Lin, Xiuyu Sun, Qian Qi, Hao Li, Rong Jin

NeurIPS 2019 Non-Asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems Yi Xu, Rong Jin, Tianbao Yang

ICML 2019 On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization Hao Yu, Rong Jin

IJCAI 2019 On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Minimization Yi Xu, Zhuoning Yuan, Sen Yang, Rong Jin, Tianbao Yang

ICML 2019 On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization Hao Yu, Rong Jin, Sen Yang

JMLR 2019 Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou

AAAI 2019 Robust Online Matching with User Arrival Distribution Drift Yu-Hang Zhou, Chen Liang, Nan Li, Cheng Yang, Shenghuo Zhu, Rong Jin

AAAI 2019 Robust Optimization over Multiple Domains Qi Qian, Shenghuo Zhu, Jiasheng Tang, Rong Jin, Baigui Sun, Hao Li

AAAI 2019 Semi-Parametric Sampling for Stochastic Bandits with Many Arms Mingdong Ou, Nan Li, Cheng Yang, Shenghuo Zhu, Rong Jin

NeurIPS 2019 Stagewise Training Accelerates Convergence of Testing Error over SGD Zhuoning Yuan, Yan Yan, Rong Jin, Tianbao Yang

ICML 2019 Stochastic Optimization for DC Functions and Non-Smooth Non-Convex Regularizers with Non-Asymptotic Convergence Yi Xu, Qi Qi, Qihang Lin, Rong Jin, Tianbao Yang

AAAI 2019 Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin

NeurIPS 2019 XNAS: Neural Architecture Search with Expert Advice Niv Nayman, Asaf Noy, Tal Ridnik, Itamar Friedman, Rong Jin, Lihi Zelnik

AAAI 2018 Extremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM Cong Leng, Zesheng Dou, Hao Li, Shenghuo Zhu, Rong Jin

NeurIPS 2018 Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Rong Jin, Tianbao Yang

NeurIPS 2018 First-Order Stochastic Algorithms for Escaping from Saddle Points in Almost Linear Time Yi Xu, Rong Jin, Tianbao Yang

IJCAI 2018 Multinomial Logit Bandit with Linear Utility Functions Mingdong Ou, Nan Li, Shenghuo Zhu, Rong Jin

ECCVW 2018 Seamless Color Mapping for 3D Reconstruction with Consumer-Grade Scanning Devices Bin Wang, Pan Pan, Qinjie Xiao, Likang Luo, Xiaofeng Ren, Rong Jin, Xiaogang Jin

AAAI 2017 A Two-Stage Approach for Learning a Sparse Model with Sharp Excess Risk Analysis Zhe Li, Tianbao Yang, Lijun Zhang, Rong Jin

IJCAI 2017 Deep Learning at Alibaba Rong Jin

COLT 2017 Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-Type of Risk Bounds Lijun Zhang, Tianbao Yang, Rong Jin

NeurIPS 2017 Improved Dynamic Regret for Non-Degenerate Functions Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou

CVPR 2017 Missing Modalities Imputation via Cascaded Residual Autoencoder Luan Tran, Xiaoming Liu, Jiayu Zhou, Rong Jin

AAAI 2016 Accelerated Sparse Linear Regression via Random Projection Weizhong Zhang, Lijun Zhang, Rong Jin, Deng Cai, Xiaofei He

AAAI 2016 Fast and Accurate Refined Nyström-Based Kernel SVM Zhe Li, Tianbao Yang, Lijun Zhang, Rong Jin

MLJ 2016 On Data Preconditioning for Regularized Loss Minimization Tianbao Yang, Rong Jin, Shenghuo Zhu, Qihang Lin

ICML 2016 Online Stochastic Linear Optimization Under One-Bit Feedback Lijun Zhang, Tianbao Yang, Rong Jin, Yichi Xiao, Zhi-hua Zhou

ALT 2016 Sparse Learning for Large-Scale and High-Dimensional Data: A Randomized Convex-Concave Optimization Approach Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou

AAAI 2016 Stochastic Optimization for Kernel PCA Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou

ICML 2016 Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi

AISTATS 2015 A Simple Homotopy Algorithm for Compressive Sensing Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou

MLJ 2015 An Efficient Primal Dual Prox Method for Non-Smooth Optimization Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Shenghuo Zhu

ICML 2015 An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu

ICML 2015 CUR Algorithm for Partially Observed Matrices Miao Xu, Rong Jin, Zhi-Hua Zhou

MLJ 2015 Efficient Distance Metric Learning by Adaptive Sampling and Mini-Batch Stochastic Gradient Descent (SGD) Qi Qian, Rong Jin, Jinfeng Yi, Lijun Zhang, Shenghuo Zhu

CVPR 2015 Fine-Grained Visual Categorization via Multi-Stage Metric Learning Qi Qian, Rong Jin, Shenghuo Zhu, Yuanqing Lin

COLT 2015 Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization Mehrdad Mahdavi, Lijun Zhang, Rong Jin

AAAI 2015 Nystrom Approximation for Sparse Kernel Methods: Theoretical Analysis and Empirical Evaluation Zenglin Xu, Rong Jin, Bin Shen, Shenghuo Zhu

AAAI 2015 Online Bandit Learning for a Special Class of Non-Convex Losses Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou

ICML 2015 Theory of Dual-Sparse Regularized Randomized Reduction Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu

ICML 2014 A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-Dimensional Data Jinfeng Yi, Lijun Zhang, Jun Wang, Rong Jin, Anil Jain

ICML 2014 Efficient Algorithms for Robust One-Bit Compressive Sensing Lijun Zhang, Jinfeng Yi, Rong Jin

UAI 2014 Efficient Sparse Recovery via Adaptive Non-Convex Regularizers with Oracle Property Ming Lin, Rong Jin, Changshui Zhang

NeurIPS 2014 Extracting Certainty from Uncertainty: Transductive Pairwise Classification from Pairwise Similarities Tianbao Yang, Rong Jin

ECCV 2014 Image Tag Completion by Noisy Matrix Recovery Zheyun Feng, Songhe Feng, Rong Jin, Anil K. Jain

AAAI 2014 Privacy and Regression Model Preserved Learning Jinfeng Yi, Jun Wang, Rong Jin

MLJ 2014 Regret Bounded by Gradual Variation for Online Convex Optimization Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Shenghuo Zhu

AAAI 2014 Sparse Learning for Stochastic Composite Optimization Weizhong Zhang, Lijun Zhang, Yao Hu, Rong Jin, Deng Cai, Xiaofei He

NeurIPS 2014 Top Rank Optimization in Linear Time Nan Li, Rong Jin, Zhi-Hua Zhou

CVPR 2013 Compressed Hashing Yue Lin, Rong Jin, Deng Cai, Shuicheng Yan, Xuelong Li

ICCV 2013 Large-Scale Image Annotation by Efficient and Robust Kernel Metric Learning Zheyun Feng, Rong Jin, Anil Jain

NeurIPS 2013 Linear Convergence with Condition Number Independent Access of Full Gradients Lijun Zhang, Mehrdad Mahdavi, Rong Jin

NeurIPS 2013 Mixed Optimization for Smooth Functions Mehrdad Mahdavi, Lijun Zhang, Rong Jin

ICML 2013 O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions Lijun Zhang, Tianbao Yang, Rong Jin, Xiaofei He

ICML 2013 One-Pass AUC Optimization Wei Gao, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou

ICML 2013 Online Kernel Learning with a near Optimal Sparsity Bound Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He

MLJ 2013 Online Multiple Kernel Classification Steven C. H. Hoi, Rong Jin, Peilin Zhao, Tianbao Yang

COLT 2013 Passive Learning with Target Risk Mehrdad Mahdavi, Rong Jin

COLT 2013 Recovering the Optimal Solution by Dual Random Projection Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang, Shenghuo Zhu

ICML 2013 Semi-Supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion Jinfeng Yi, Lijun Zhang, Rong Jin, Qi Qian, Anil Jain

NeurIPS 2013 Speedup Matrix Completion with Side Information: Application to Multi-Label Learning Miao Xu, Rong Jin, Zhi-Hua Zhou

NeurIPS 2013 Stochastic Convex Optimization with Multiple Objectives Mehrdad Mahdavi, Tianbao Yang, Rong Jin

ICML 2012 A Simple Algorithm for Semi-Supervised Learning with Improved Generalization Error Bound Ming Ji, Tianbao Yang, Binbin Lin, Rong Jin, Jiawei Han

AAAI 2012 Efficient Online Learning for Large-Scale Sparse Kernel Logistic Regression Lijun Zhang, Rong Jin, Chun Chen, Jiajun Bu, Xiaofei He

ICML 2012 Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning Steven C. H. Hoi, Jialei Wang, Peilin Zhao, Rong Jin, Pengcheng Wu

ICML 2012 Multiple Kernel Learning from Noisy Labels by Stochastic Programming Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou

NeurIPS 2012 Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison Tianbao Yang, Yu-feng Li, Mehrdad Mahdavi, Rong Jin, Zhi-Hua Zhou

AAAI 2012 Online Kernel Selection: Algorithms and Evaluations Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Yi, Steven C. H. Hoi

COLT 2012 Online Optimization with Gradual Variations Chao-Kai Chiang, Tianbao Yang, Chia-Jung Lee, Mehrdad Mahdavi, Chi-Jen Lu, Rong Jin, Shenghuo Zhu

AAAI 2012 Random Projection with Filtering for Nearly Duplicate Search Yue Lin, Rong Jin, Deng Cai, Xiaofei He

NeurIPS 2012 Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning Jinfeng Yi, Rong Jin, Shaili Jain, Tianbao Yang, Anil K. Jain

NeurIPS 2012 Stochastic Gradient Descent with Only One Projection Mehrdad Mahdavi, Tianbao Yang, Rong Jin, Shenghuo Zhu, Jinfeng Yi

JMLR 2012 Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints Mehrdad Mahdavi, Rong Jin, Tianbao Yang

CVPR 2011 A Probabilistic Representation for Efficient Large Scale Visual Recognition Tasks Subhabrata Bhattacharya, Rahul Sukthankar, Rong Jin, Mubarak Shah

MLJ 2011 Detecting Communities and Their Evolutions in Dynamic Social Networks - A Bayesian Approach Tianbao Yang, Yun Chi, Shenghuo Zhu, Yihong Gong, Rong Jin

JMLR 2011 Double Updating Online Learning Peilin Zhao, Steven C.H. Hoi, Rong Jin

CVPR 2011 Multi-Label Learning with Incomplete Class Assignments Serhat Selcuk Bucak, Rong Jin, Anil K. Jain

AAAI 2011 Multi-Task Learning in Square Integrable Space Wei Wu, Hang Li, Yunhua Hu, Rong Jin

ICML 2011 Online AUC Maximization Peilin Zhao, Steven C. H. Hoi, Rong Jin, Tianbao Yang

AISTATS 2010 A Potential-Based Framework for Online Multi-Class Learning with Partial Feedback Shijun Wang, Rong Jin, Hamed Valizadegan

NeurIPS 2010 Active Learning by Querying Informative and Representative Examples Sheng-jun Huang, Rong Jin, Zhi-Hua Zhou

AISTATS 2010 Exclusive Lasso for Multi-Task Feature Selection Yang Zhou, Rong Jin, Steven Chu–Hong Hoi

ICML 2010 Learning from Noisy Side Information by Generalized Maximum Entropy Model Tianbao Yang, Rong Jin, Anil K. Jain

NeurIPS 2010 Multi-Label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition Serhat Bucak, Rong Jin, Anil K. Jain

ALT 2010 Online Multiple Kernel Learning: Algorithms and Mistake Bounds Rong Jin, Steven C. H. Hoi, Tianbao Yang

CVPR 2010 Online Visual Vocabulary Pruning Using Pairwise Constraints Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain

UAI 2010 Robust Metric Learning by Smooth Optimization Kaizhu Huang, Rong Jin, Zenglin Xu, Cheng-Lin Liu

ICML 2010 Simple and Efficient Multiple Kernel Learning by Group Lasso Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King, Michael R. Lyu

AAAI 2010 Smooth Optimization for Effective Multiple Kernel Learning Zenglin Xu, Rong Jin, Shenghuo Zhu, Michael R. Lyu, Irwin King

UAI 2009 A Bayesian Framework for Community Detection Integrating Content and Link Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu

NeurIPS 2009 Adaptive Regularization for Transductive Support Vector Machine Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael Lyu, Zhirong Yang

AISTATS 2009 An Information Geometry Approach for Distance Metric Learning Shijun Wang, Rong Jin

NeurIPS 2009 DUOL: A Double Updating Approach for Online Learning Peilin Zhao, Steven C. Hoi, Rong Jin

IJCAI 2009 Discriminative Semi-Supervised Feature Selection via Manifold Regularization Zenglin Xu, Rong Jin, Michael R. Lyu, Irwin King

ICCV 2009 Efficient Multi-Label Ranking for Multi-Class Learning: Application to Object Recognition Serhat Selcuk Bucak, Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain

NeurIPS 2009 Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering Lei Wu, Rong Jin, Steven C. Hoi, Jianke Zhu, Nenghai Yu

CVPR 2009 Learning a Distance Metric from Multi-Instance Multi-Label Data Rong Jin, Shijun Wang, Zhi-Hua Zhou

NeurIPS 2009 Learning to Rank by Optimizing NDCG Measure Hamed Valizadegan, Rong Jin, Ruofei Zhang, Jianchang Mao

ICML 2009 Non-Monotonic Feature Selection Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, Irwin King

ICML 2009 Online Learning by Ellipsoid Method Liu Yang, Rong Jin, Jieping Ye

NeurIPS 2009 Regularized Distance Metric Learning:Theory and Algorithm Rong Jin, Shijun Wang, Yang Zhou

ICML 2008 Active Kernel Learning Steven C. H. Hoi, Rong Jin

NeurIPS 2008 An Extended Level Method for Efficient Multiple Kernel Learning Zenglin Xu, Rong Jin, Irwin King, Michael Lyu

NeurIPS 2008 Multi-Label Multiple Kernel Learning Shuiwang Ji, Liang Sun, Rong Jin, Jieping Ye

CVPR 2008 Rank-Based Distance Metric Learning: An Application to Image Retrieval Jung-Eun Lee, Rong Jin, Anil K. Jain

ECML-PKDD 2008 Semi-Supervised Boosting for Multi-Class Classification Hamed Valizadegan, Rong Jin, Anil K. Jain

AAAI 2008 Semi-Supervised Ensemble Ranking Steven C. H. Hoi, Rong Jin

NeurIPS 2008 Semi-Supervised Learning with Weakly-Related Unlabeled Data : Towards Better Text Categorization Liu Yang, Rong Jin, Rahul Sukthankar

CVPR 2008 Semi-Supervised SVM Batch Mode Active Learning for Image Retrieval Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu

CVPR 2008 Unifying Discriminative Visual Codebook Generation with Classifier Training for Object Category Recognition Liu Yang, Rong Jin, Rahul Sukthankar, Frédéric Jurie

AAAI 2008 Using Knowledge Driven Matrix Factorization to Reconstruct Modular Gene Regulatory Network Yang Zhou, Zheng Li, Xuerui Yang, Linxia Zhang, Shireesh Srivastava, Rong Jin, Christina Chan

AAAI 2007 Active Algorithm Selection Feilong Chen, Rong Jin

UAI 2007 Bayesian Active Distance Metric Learning Liu Yang, Rong Jin, Rahul Sukthankar

CVPR 2007 Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data Liu Yang, Rong Jin, Caroline Pantofaru, Rahul Sukthankar

NeurIPS 2007 Efficient Convex Relaxation for Transductive Support Vector Machine Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael Lyu

ICML 2007 Learning Nonparametric Kernel Matrices from Pairwise Constraints Steven C. H. Hoi, Rong Jin, Michael R. Lyu

MLJ 2007 Multi-Class Learning by Smoothed Boosting Rong Jin, Jian Zhang

AAAI 2007 Semi-Supervised Learning by Mixed Label Propagation Wei Tong, Rong Jin

AAAI 2006 An Efficient Algorithm for Local Distance Metric Learning Liu Yang, Rong Jin, Rahul Sukthankar, Yi Liu

ICML 2006 Batch Mode Active Learning and Its Application to Medical Image Classification Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu

CVPR 2006 Correlated Label Propagation with Application to Multi-Label Learning Feng Kang, Rong Jin, Rahul Sukthankar

NeurIPS 2006 Generalized Maximum Margin Clustering and Unsupervised Kernel Learning Hamed Valizadegan, Rong Jin

AAAI 2006 Semi-Supervised Multi-Label Learning by Constrained Non-Negative Matrix Factorization Yi Liu, Rong Jin, Liu Yang

IJCAI 2005 A Novel Approach to Model Generation for Heterogeneous Data Classification Rong Jin, Huan Liu

NeurIPS 2005 A Probabilistic Approach for Optimizing Spectral Clustering Rong Jin, Feng Kang, Chris H. Ding

ICML 2005 A Smoothed Boosting Algorithm Using Probabilistic Output Codes Rong Jin, Jian Zhang

ICML 2005 Learn to Weight Terms in Information Retrieval Using Category Information Rong Jin, Joyce Y. Chai, Luo Si

IJCAI 2005 Learning with Labeled Sessions Rong Jin, Huan Liu

AAAI 2005 Query Translation Disambiguation as Graph Partitioning Yi Liu, Rong Jin

UAI 2004 A Bayesian Approach Toward Active Learning for Collaborative Filtering Rong Jin, Luo Si

ICML 2004 Robust Feature Induction for Support Vector Machines Rong Jin, Huan Liu

ECML-PKDD 2004 SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data Rong Jin, Huan Liu

ICML 2003 A Faster Iterative Scaling Algorithm for Conditional Exponential Model Rong Jin, Rong Yan, Jian Zhang, Alexander G. Hauptmann

ECML-PKDD 2003 A New Pairwise Ensemble Approach for Text Classification Yan Liu, Jaime G. Carbonell, Rong Jin

ICML 2003 Flexible Mixture Model for Collaborative Filtering Luo Si, Rong Jin

ICML 2003 Modified Logistic Regression: An Approximation to SVM and Its Applications in Large-Scale Text Categorization Jian Zhang, Rong Jin, Yiming Yang, Alexander G. Hauptmann

UAI 2003 Preference-Based Graphic Models for Collaborative Filtering Rong Jin, Luo Si, ChengXiang Zhai

NeurIPS 2002 Learning with Multiple Labels Rong Jin, Zoubin Ghahramani

ICML 2001 Learning to Select Good Title Words: An New Approach Based on Reverse Information Retrieval Rong Jin, Alexander G. Hauptmann

IJCAI 2001 Title Generation for Machine-Translated Documents Rong Jin, Alexander G. Hauptmann