Rong Jin - RankMe

518 papers A* 170A 33B 13C 1Misc 3Journal 218Unranked 75

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates. CoRR Linxiao Yang, Xue Jiang, Gezheng Xu, Tian Zhou, Min Yang, Zhaoyang Zhu, Linyuan Geng, Zhipeng Zeng, Qiming Chen, Xinyue Gu, Rong Jin, Liang Sun
2026	J	`jnl`	Beyond LLaVA-HD: Diving Into High-Resolution Multimodal Large Language Models. IEEE Trans. Pattern Anal. Mach. Intell. Yifan Zhang, Qingsong Wen, Chaoyou Fu, Kun Wang, Xue Wang, Zhang Zhang, Liang Wang, Rong Jin
2026	J	`jnl`	Feed m Birds with One Scone: Accelerating Multi-task Gradient Balancing via Bi-level Optimization. CoRR Xuxing Chen, Yun He, Jiayi Xu, Minhui Huang, Xiaoyi Liu, Boyang Liu, Fei Tian, Xiaohan Wei, Rong Jin, Sem Park, Bo Long, Xue Feng
2026	A*	`conf`	Mixture of Sequence: Theme-Aware Mixture-of-Experts for Long-Sequence Recommendation. WWW Xiao Lin, Zhicheng Tang, Weilin Cong, Mengyue Hang, Kai Wang, Yajuan Wang, Zhichen Zeng, Ting-Wei Li, Hyunsik Yoo, Zhining Liu, Xuying Ning, Ruizhong Qiu, Wen-Yen Chen, Shuo Chang, Rong Jin, Huayu Li, Hanghang Tong
2026	J	`jnl`	Model-Free Test Time Adaptation for Out-of-Distribution Detection. IEEE Trans. Pattern Anal. Mach. Intell. Yifan Zhang, Xue Wang, Tian Zhou, Kun Yuan, Zhang Zhang, Liang Wang, Rong Jin
2025	J	`jnl`	Bridging Past and Future: Distribution-Aware Alignment for Time Series Forecasting. CoRR Yifan Hu, Jie Yang, Tian Zhou, Peiyuan Liu, Yujin Tang, Rong Jin, Liang Sun
2025	J	`jnl`	Cross-attention Secretly Performs Orthogonal Alignment in Recommendation Models. CoRR Hyunin Lee, Yong Zhang, Hoang Vu Nguyen, Xiaoyi Liu, Namyong Park, Christopher Jung, Rong Jin, Yang Wang, Zhigang Wang, Somayeh Sojoudi, Xue Feng
2025	A*	`conf`	Debiasing Multimodal Large Language Models via Penalization of Language Priors. ACM Multimedia Yifan Zhang, Yang Shi, Weichen Yu, Qingsong Wen, Xue Wang, Wenjing Yang, Zhang Zhang, Liang Wang, Rong Jin
2025	—	`conf`	Does Vector Quantization Fail in Spatio-Temporal Forecasting? Exploring a Differentiable Sparse Soft-Vector Quantization Approach. KDD (2) Chao Chen, Tian Zhou, Yanjun Zhao, Hui Liu, Rong Jin, Liang Sun
2025	A	`conf`	Enhancing Embedding Representation Stability in Recommendation Systems with Semantic ID. RecSys Carolina Zheng, Minhui Huang, Dmitrii Pedchenko, Kaushik Rangadurai, Siyu Wang, Fan Xia, Gaby Nahum, Jie Lei, Yang Yang, Tao Liu, Zutian Luo, Xiaohan Wei, Dinesh Ramasamy, Jiyan Yang, Yiping Han, Lin Yang, Hangjun Xu, Rong Jin, Shuang Yang
2025	J	`jnl`	Enhancing Embedding Representation Stability in Recommendation Systems with Semantic ID. CoRR Carolina Zheng, Minhui Huang, Dmitrii Pedchenko, Kaushik Rangadurai, Siyu Wang, Gaby Nahum, Jie Lei, Yang Yang, Tao Liu, Zutian Luo, Xiaohan Wei, Dinesh Ramasamy, Jiyan Yang, Yiping Han, Lin Yang, Hangjun Xu, Rong Jin, Shuang Yang
2025	—	`conf`	External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation. WWW (Companion Volume) Mingfu Liang, Xi Liu, Rong Jin, Boyang Liu, Qiuling Suo, Qinghai Zhou, Song Zhou, Laming Chen, Hua Zheng, Zhiyuan Li, Shali Jiang, Jiyan Yang, Xiaozhen Xia, Fan Yang, Yasmine Badr, Ellie Wen, Shuyu Xu, Hansey Chen, Zhengyu Zhang, Jade Nie, Chunzhi Yang, Zhichen Zeng, Weilin Zhang, Xingliang Huang, Qianru Li, Shiquan Wang, Evelyn Lyu, Wenjing Lu, Rui Zhang, Wenjun Wang, Jason Rudy, Mengyue Hang, Kai Wang, Bo Long, Wenlin Chen, Santanu Kolay, Huayu Li
2025	J	`jnl`	External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation. CoRR Mingfu Liang, Xi Liu, Rong Jin, Boyang Liu, Qiuling Suo, Qinghai Zhou, Song Zhou, Laming Chen, Hua Zheng, Zhiyuan Li, Shali Jiang, Jiyan Yang, Xiaozhen Xia, Fan Yang, Yasmine Badr, Ellie Wen, Shuyu Xu, Hansey Chen, Zhengyu Zhang, Jade Nie, Chunzhi Yang, Zhichen Zeng, Weilin Zhang, Xingliang Huang, Qianru Li, Shiquan Wang, Evelyn Lyu, Wenjing Lu, Rui Zhang, Wenjun Wang, Jason Rudy, Mengyue Hang, Kai Wang, Yinbin Ma, Shuaiwen Wang, Sihan Zeng, Tongyi Tang, Xiaohan Wei, Longhao Jin, Jamey Zhang, Marcus Chen, Jiayi Zhang, Angie Huang, Chi Zhang, Zhengli Zhao, Jared Yang, Qiang Jin, Xian Chen, Amit Anand Amlesahwaram, Lexi Song, Liang Luo, Yuchen Hao, Nan Xiao, Yavuz Yetim, Luoshang Pan, Gaoxiang Liu, Yuxi Hu, Yuzhen Huang, Jackie Xu, Rich Zhu, Xin Zhang, Yiqun Liu, Hang Yin, Yuxin Chen, Buyun Zhang, Xiaoyi Liu, Xingyuan Wang, Wenguang Mao, Zhijing Li, Qin Huang, Chonglin Sun, Shupin Mao, Benjamin Au, Jingzheng Qin, Peggy Yao, Jae-Woo Choi, Bin Gao, Ernest Wang, Lei Zhang, Wen-Yen Chen, Ted Lee, Jay Zha, Yi Meng, Alex Gong, Edison Gao, Alireza Vahdatpour, Yiping Han, Yantao Yao, Toshinari Kureha, Shuo Chang, Musharaf Sultan, John Bocharov, Sagar Chordia, Xiaorui Gan, Peng Sun, Rocky Liu, Bo Long, Wenlin Chen, Santanu Kolay, Huayu Li
2025	A*	`conf`	MM-RLHF: The Next Step Forward in Multimodal LLM Alignment. ICML 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
2025	J	`jnl`	MM-RLHF: The Next Step Forward in Multimodal LLM Alignment. CoRR 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, Fan Yang, Zhang Zhang, Tingting Gao, Di Zhang, Liang Wang, Rong Jin, Tieniu Tan
2025	A*	`conf`	MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? ICLR Yifan Zhang, Huanyu Zhang, Haochen Tian, Chaoyou Fu, Shuangqing Zhang, Junfei Wu, Feng Li, Kun Wang, Qingsong Wen, Zhang Zhang, Liang Wang, Rong Jin
2025	Misc	`conf`	Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series. ICASSP Yanjun Zhao, Tian Zhou, Chao Chen, Liang Sun, Yi Qian, Rong Jin
2025	J	`jnl`	Unified convergence analysis for adaptive optimization with moving average estimator. Mach. Learn. Zhishuai Guo, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang
2025	—	`conf`	Utilizing Strategic Pre-training to Reduce Overfitting: Baguan - A Pre-trained Weather Forecasting Model. KDD (2) Peisong Niu, Ziqing Ma, Tian Zhou, Weiqi Chen, Lefei Shen, Rong Jin, Liang Sun
2025	J	`jnl`	Utilizing Strategic Pre-training to Reduce Overfitting: Baguan - A Pre-trained Weather Forecasting Model. CoRR Peisong Niu, Ziqing Ma, Tian Zhou, Weiqi Chen, Lefei Shen, Rong Jin, Liang Sun
2024	J	`jnl`	A Collaborative Ensemble Framework for CTR Prediction. CoRR Xiaolong Liu, Zhichen Zeng, Xiaoyi Liu, Siyang Yuan, Weinan Song, Mengyue Hang, Yiqun Liu, Chaofei Yang, Donghyun Kim, Wen-Yen Chen, Jiyan Yang, Yiping Han, Rong Jin, Bo Long, Hanghang Tong, Philip S. Yu
2024	J	`jnl`	Addressing Concept Shift in Online Time Series Forecasting: Detect-then-Adapt. CoRR Yifan Zhang, Weiqi Chen, Zhaoyang Zhu, Dalin Qin, Liang Sun, Xue Wang, Qingsong Wen, Zhang Zhang, Liang Wang, Rong Jin
2024	J	`jnl`	Attention as Robust Representation for Time Series Forecasting. CoRR Peisong Niu, Tian Zhou, Xue Wang, Liang Sun, Rong Jin
2024	J	`jnl`	Beyond LLaVA-HD: Diving into High-Resolution Large Multimodal Models. CoRR Yifan Zhang, Qingsong Wen, Chaoyou Fu, Xue Wang, Zhang Zhang, Liang Wang, Rong Jin
2024	A*	`conf`	CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting. ICLR Xue Wang, Tian Zhou, Qingsong Wen, Jinyang Gao, Bolin Ding, Rong Jin
2024	J	`jnl`	Debiasing Multimodal Large Language Models. CoRR Yifan Zhang, Weichen Yu, Qingsong Wen, Xue Wang, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
2024	J	`jnl`	Efficient LLM-Jailbreaking by Introducing Visual Modality. CoRR Zhenxing Niu, Yuyao Sun, Haodong Ren, Haoxuan Ji, Quan Wang, Xiaoke Ma, Gang Hua, Rong Jin
2024	A	`conf`	EmbSum: Leveraging the Summarization Capabilities of Large Language Models for Content-Based Recommendations. RecSys Chiyu Zhang, Yifei Sun, Minghao Wu, Jun Chen, Jie Lei, Muhammad Abdul-Mageed, Rong Jin, Angli Liu, Ji Zhu, Sem Park, Ning Yao, Bo Long
2024	J	`jnl`	EmbSum: Leveraging the Summarization Capabilities of Large Language Models for Content-Based Recommendations. CoRR Chiyu Zhang, Yifei Sun, Minghao Wu, Jun Chen, Jie Lei, Muhammad Abdul-Mageed, Rong Jin, Angli Liu, Ji Zhu, Sem Park, Ning Yao, Bo Long
2024	A*	`conf`	FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting. KDD Ziqing Ma, Wenwei Wang, Tian Zhou, Chao Chen, Bingqing Peng, Liang Sun, Rong Jin
2024	J	`jnl`	FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting. CoRR Ziqing Ma, Wenwei Wang, Tian Zhou, Chao Chen, Bingqing Peng, Liang Sun, Rong Jin
2024	J	`jnl`	HyRSM++: Hybrid relation guided temporal set matching for few-shot action recognition. Pattern Recognit. Xiang Wang, Shiwei Zhang, Zhiwu Qing, Zhengrong Zuo, Changxin Gao, Rong Jin, Nong Sang
2024	J	`jnl`	Jailbreaking Attack against Multimodal Large Language Model. CoRR Zhenxing Niu, Haodong Ren, Xinbo Gao, Gang Hua, Rong Jin
2024	J	`jnl`	MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? CoRR Yifan Zhang, Huanyu Zhang, Haochen Tian, Chaoyou Fu, Shuangqing Zhang, Junfei Wu, Feng Li, Kun Wang, Qingsong Wen, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
2024	J	`jnl`	Maximizing the Impact of Deep Learning on Subseasonal-to-Seasonal Climate Forecasting: The Essential Role of Optimization. CoRR Yizhen Guo, Tian Zhou, Wanyi Jiang, Bo Wu, Liang Sun, Rong Jin
2024	J	`jnl`	Mitigating Time Discretization Challenges with WeatherODE: A Sandwich Physics-Driven Neural ODE for Weather Forecasting. CoRR Peiyuan Liu, Tian Zhou, Liang Sun, Rong Jin
2024	J	`jnl`	MultiBalance: Multi-Objective Gradient Balancing in Industrial-Scale Multi-Task Recommendation System. CoRR Yun He, Xuxing Chen, Jiayi Xu, Renqin Cai, Yiling You, Jennifer Cao, Minhui Huang, Liu Yang, Yiqun Liu, Xiaoyi Liu, Rong Jin, Sem Park, Bo Long, Xue Feng
2024	J	`jnl`	S CoRR Xue Wang, Tian Zhou, Jianqing Zhu, Jialin Liu, Kun Yuan, Tao Yao, Wotao Yin, Rong Jin, HanQin Cai
2024	J	`jnl`	S$^\text{3}$Attention: Improving Long Sequence Attention With Smoothed Skeleton Sketching. IEEE J. Sel. Top. Signal Process. Xue Wang, Tian Zhou, Jianqing Zhu, Jialin Liu, Kun Yuan, Tao Yao, Wotao Yin, Rong Jin, HanQin Cai
2024	J	`jnl`	SPAR: Personalized Content-Based Recommendation via Long Engagement Attention. CoRR Chiyu Zhang, Yifei Sun, Jun Chen, Jie Lei, Muhammad Abdul-Mageed, Sinong Wang, Rong Jin, Sem Park, Ning Yao, Bo Long
2024	J	`jnl`	Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting. CoRR Yanjun Zhao, Tian Zhou, Chao Chen, Liang Sun, Yi Qian, Rong Jin
2024	A*	`conf`	Structured Model Probing: Empowering Efficient Transfer Learning by Structured Regularization. CVPR Zhi-Fan Wu, Chaojie Mao, Xue Wang, Jianwen Jiang, Yiliang Lv, Rong Jin
2024	J	`jnl`	Towards Aligned Data Removal via Twin Machine Unlearning. CoRR Yuyao Sun, Zhenxing Niu, Gang Hua, Rong Jin
2024	J	`jnl`	Towards Unified Robustness Against Both Backdoor and Adversarial Attacks. CoRR Zhenxing Niu, Yuyao Sun, Qiguang Miao, Rong Jin, Gang Hua
2024	J	`jnl`	Towards Unified Robustness Against Both Backdoor and Adversarial Attacks. IEEE Trans. Pattern Anal. Mach. Intell. Zhenxing Niu, Yuyao Sun, Qiguang Miao, Rong Jin, Gang Hua
2024	A*	`conf`	UNICORN: A Unified Causal Video-Oriented Language-Modeling Framework for Temporal Video-Language Tasks. EMNLP Yuanhao Xiong, Yixin Nie, Haotian Liu, Boxin Wang, Jun Chen, Rong Jin, Cho-Jui Hsieh, Lorenzo Torresani, Jie Lei
2023	J	`jnl`	Achieving Human Parity on Visual Question Answering. ACM Trans. Inf. Syst. Ming Yan, Haiyang Xu, Chenliang Li, Junfeng Tian, Bin Bi, Wei Wang, Xianzhe Xu, Ji Zhang, Songfang Huang, Fei Huang, Luo Si, Rong Jin
2023	A*	`conf`	AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation. ICML Yifan Zhang, Xue Wang, Kexin Jin, Kun Yuan, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
2023	J	`jnl`	AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation. CoRR Yifan Zhang, Xue Wang, Kexin Jin, Kun Yuan, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
2023	J	`jnl`	Assaying on the Robustness of Zero-Shot Machine-Generated Text Detectors. CoRR Yifan Zhang, Zhang Zhang, Liang Wang, Tieniu Tan, Rong Jin
2023	J	`jnl`	Attentional-Biased Stochastic Gradient Descent. Trans. Mach. Learn. Res. Qi Qi, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang
2023	A*	`conf`	Beyond Appearance: A Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks. CVPR Weihua Chen, Xianzhe Xu, Jian Jia, Hao Luo, Yaohua Wang, Fan Wang, Rong Jin, Xiuyu Sun
2023	J	`jnl`	Beyond Appearance: a Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks. CoRR Weihua Chen, Xianzhe Xu, Jian Jia, Hao Luo, Yaohua Wang, Fan Wang, Rong Jin, Xiuyu Sun
2023	A*	`conf`	FeDXL: Provable Federated Learning for Deep X-Risk Optimization. ICML Zhishuai Guo, Rong Jin, Jiebo Luo, Tianbao Yang
2023	A*	`conf`	Free Lunch for Domain Adversarial Training: Environment Label Smoothing. ICLR Yifan Zhang, Xue Wang, Jian Liang, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
2023	J	`jnl`	Free Lunch for Domain Adversarial Training: Environment Label Smoothing. CoRR Yifan Zhang, Xue Wang, Jian Liang, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
2023	J	`jnl`	HyRSM++: Hybrid Relation Guided Temporal Set Matching for Few-shot Action Recognition. CoRR Xiang Wang, Shiwei Zhang, Zhiwu Qing, Zhengrong Zuo, Changxin Gao, Rong Jin, Nong Sang
2023	J	`jnl`	Make Transformer Great Again for Time Series Forecasting: Channel Aligned Robust Dual Transformer. CoRR Xue Wang, Tian Zhou, Qingsong Wen, Jinyang Gao, Bolin Ding, Rong Jin
2023	A*	`conf`	Making Vision Transformers Efficient from A Token Sparsification View. CVPR Shuning Chang, Pichao Wang, Ming Lin, Fan Wang, David Junhao Zhang, Rong Jin, Mike Zheng Shou
2023	J	`jnl`	Making Vision Transformers Efficient from A Token Sparsification View. CoRR Shuning Chang, Pichao Wang, Ming Lin, Fan Wang, David Junhao Zhang, Rong Jin, Mike Zheng Shou
2023	J	`jnl`	Model-free Test Time Adaptation for Out-Of-Distribution Detection. CoRR Yifan Zhang, Xue Wang, Tian Zhou, Kun Yuan, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
2023	A*	`conf`	One Fits All: Power General Time Series Analysis by Pretrained LM. NeurIPS Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, Rong Jin
2023	J	`jnl`	One Fits All: Universal Time Series Analysis by Pretrained LM and Specially Designed Adaptors. CoRR Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, Rong Jin
2023	A*	`conf`	OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling. NeurIPS Yifan Zhang, Qingsong Wen, Xue Wang, Weiqi Chen, Liang Sun, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
2023	J	`jnl`	OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling. CoRR Yifan Zhang, Qingsong Wen, Xue Wang, Weiqi Chen, Liang Sun, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
2023	J	`jnl`	ParamCrop: Parametric Cubic Cropping for Video Contrastive Learning. IEEE Trans. Multim. Zhiwu Qing, Ziyuan Huang, Shiwei Zhang, Mingqian Tang, Changxin Gao, Rong Jin, Marcelo H. Ang, Nong Sang
2023	J	`jnl`	Power Time Series Forecasting by Pretrained LM. CoRR Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, Rong Jin
2023	A*	`conf`	Progressive Backdoor Erasing via connecting Backdoor and Adversarial Attacks. CVPR Bingxu Mu, Zhenxing Niu, Le Wang, Xue Wang, Qiguang Miao, Rong Jin, Gang Hua
2023	J	`jnl`	SVQ: Sparse Vector Quantization for Spatiotemporal Forecasting. CoRR Chao Chen, Tian Zhou, Yanjun Zhao, Hui Liu, Liang Sun, Rong Jin
2023	J	`jnl`	Self-Supervised Learning from Untrimmed Videos via Hierarchical Consistency. IEEE Trans. Pattern Anal. Mach. Intell. Zhiwu Qing, Shiwei Zhang, Ziyuan Huang, Yi Xu, Xiang Wang, Changxin Gao, Rong Jin, Nong Sang
2023	J	`jnl`	What Limits the Performance of Local Self-attention? Int. J. Comput. Vis. Jingkai Zhou, Pichao Wang, Jiasheng Tang, Fan Wang, Qiong Liu, Hao Li, Rong Jin
2022	A*	`conf`	A Trend-Driven Fashion Design System for Rapid Response Marketing in E-commerce. AAAI Lianghua Huang, Yu Liu, Bin Wang, Pan Pan, Rong Jin
2022	J	`jnl`	An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation. CoRR Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Rong Jin, Xiangyang Ji, Antoni B. Chan
2022	A*	`conf`	CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation. ICLR Tongkun Xu, Weihua Chen, Pichao Wang, Fan Wang, Hao Li, Rong Jin
2022	A*	`conf`	CHEX: CHannel EXploration for CNN Model Compression. CVPR Zejiang Hou, Minghai Qin, Fei Sun, Xiaolong Ma, Kun Yuan, Yi Xu, Yen-Kuang Chen, Rong Jin, Yuan Xie, Sun-Yuan Kung
2022	J	`jnl`	CHEX: CHannel EXploration for CNN Model Compression. CoRR Zejiang Hou, Minghai Qin, Fei Sun, Xiaolong Ma, Kun Yuan, Yi Xu, Yen-Kuang Chen, Rong Jin, Yuan Xie, Sun-Yuan Kung
2022	A*	`conf`	Decoupling and Recoupling Spatiotemporal Representation for RGB-D-based Motion Recognition. CVPR Benjia Zhou, Pichao Wang, Jun Wan, Yanyan Liang, Fan Wang, Du Zhang, Zhen Lei, Hao Li, Rong Jin
2022	A*	`conf`	Effective Model Sparsification by Scheduled Grow-and-Prune Methods. ICLR Xiaolong Ma, Minghai Qin, Fei Sun, Zejiang Hou, Kun Yuan, Yi Xu, Yanzhi Wang, Yen-Kuang Chen, Rong Jin, Yuan Xie
2022	A*	`conf`	Entroformer: A Transformer-based Entropy Model for Learned Image Compression. ICLR Yichen Qian, Xiuyu Sun, Ming Lin, Zhiyu Tan, Rong Jin
2022	J	`jnl`	Entroformer: A Transformer-based Entropy Model for Learned Image Compression. CoRR Yichen Qian, Ming Lin, Xiuyu Sun, Zhiyu Tan, Rong Jin
2022	A*	`conf`	FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting. ICML Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, Rong Jin
2022	J	`jnl`	FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting. CoRR Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, Rong Jin
2022	J	`jnl`	FedX: Federated Learning for Compositional Pairwise Risk Optimization. CoRR Zhishuai Guo, Rong Jin, Jiebo Luo, Tianbao Yang
2022	A*	`conf`	FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting. NeurIPS Tian Zhou, Ziqing Ma, Xue Wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin
2022	J	`jnl`	FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting. CoRR Tian Zhou, Ziqing Ma, Xue Wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin
2022	Misc	`conf`	Graph Convolution for Re-Ranking in Person Re-Identification. ICASSP Yuqi Zhang, Qi Qian, Chong Liu, Weihua Chen, Fan Wang, Hao Li, Rong Jin
2022	A*	`conf`	Grow and Merge: A Unified Framework for Continuous Categories Discovery. NeurIPS Xinwei Zhang, Jianwen Jiang, Yutong Feng, Zhi-Fan Wu, Xibin Zhao, Hai Wan, Mingqian Tang, Rong Jin, Yue Gao
2022	J	`jnl`	Grow and Merge: A Unified Framework for Continuous Categories Discovery. CoRR Xinwei Zhang, Jianwen Jiang, Yutong Feng, Zhi-Fan Wu, Xibin Zhao, Hai Wan, Mingqian Tang, Rong Jin, Yue Gao
2022	A*	`conf`	Hybrid Relation Guided Set Matching for Few-shot Action Recognition. CVPR Xiang Wang, Shiwei Zhang, Zhiwu Qing, Mingqian Tang, Zhengrong Zuo, Changxin Gao, Rong Jin, Nong Sang
2022	J	`jnl`	Hybrid Relation Guided Set Matching for Few-shot Action Recognition. CoRR Xiang Wang, Shiwei Zhang, Zhiwu Qing, Mingqian Tang, Zhengrong Zuo, Changxin Gao, Rong Jin, Nong Sang
2022	A*	`conf`	Improved Fine-Tuning by Better Leveraging Pre-Training Data. NeurIPS Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Xiangyang Ji, Antoni B. Chan, Rong Jin
2022	—	`conf`	KVT: k-NN Attention for Boosting Vision Transformers. ECCV (24) Pichao Wang, Xue Wang, Fan Wang, Ming Lin, Shuning Chang, Hao Li, Rong Jin
2022	A*	`conf`	Learning from Untrimmed Videos: Self-Supervised Video Representation Learning with Hierarchical Consistency. CVPR Zhiwu Qing, Shiwei Zhang, Ziyuan Huang, Yi Xu, Xiang Wang, Mingqian Tang, Changxin Gao, Rong Jin, Nong Sang
2022	J	`jnl`	Learning from Untrimmed Videos: Self-Supervised Video Representation Learning with Hierarchical Consistency. CoRR Zhiwu Qing, Shiwei Zhang, Ziyuan Huang, Yi Xu, Xiang Wang, Mingqian Tang, Changxin Gao, Rong Jin, Nong Sang
2022	A*	`conf`	MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection. ICML Zhenhong Sun, Ming Lin, Xiuyu Sun, Zhiyu Tan, Hao Li, Rong Jin
2022	A*	`conf`	Rethinking Supervised Pre-Training for Better Downstream Transferring. ICLR Yutong Feng, Jianwen Jiang, Mingqian Tang, Rong Jin, Yue Gao
2022	J	`jnl`	Robust Graph Structure Learning over Images via Multiple Statistical Tests. CoRR Yaohua Wang, Fangyi Zhang, Ming Lin, Senzhang Wang, Xiuyu Sun, Rong Jin
2022	A*	`conf`	Robust Graph Structure Learning via Multiple Statistical Tests. NeurIPS Yaohua Wang, Fangyi Zhang, Ming Lin, Senzhang Wang, Xiuyu Sun, Rong Jin
2022	A*	`conf`	Scaled ReLU Matters for Training Vision Transformers. AAAI Pichao Wang, Xue Wang, Hao Luo, Jingkai Zhou, Zhipeng Zhou, Fan Wang, Hao Li, Rong Jin
2022	—	`conf`	TransFGU: A Top-Down Approach to Fine-Grained Unsupervised Semantic Segmentation. ECCV (29) Zhaoyuan Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li, Rong Jin
2022	J	`jnl`	TreeDRNet: A Robust Deep Model for Long Term Time Series Forecasting. CoRR Tian Zhou, Jianqing Zhu, Xue Wang, Ziqing Ma, Qingsong Wen, Liang Sun, Rong Jin
2022	A*	`conf`	Unsupervised Visual Representation Learning by Online Constrained K-Means. CVPR Qi Qian, Yuanhong Xu, Juhua Hu, Hao Li, Rong Jin
2021	J	`jnl`	A Novel Convergence Analysis for Algorithms of the Adam Family. CoRR Zhishuai Guo, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang
2021	J	`jnl`	A Theoretical Analysis of Learning with Noisily Labeled Data. CoRR Yi Xu, Qi Qian, Hao Li, Rong Jin
2021	J	`jnl`	ANN Softmax: Acceleration of Extreme Classification Training. Proc. VLDB Endow. Kang Zhao, Liuyihan Song, Yingya Zhang, Pan Pan, Yinghui Xu, Rong Jin
2021	J	`jnl`	Achieving Human Parity on Visual Question Answering. CoRR Ming Yan, Haiyang Xu, Chenliang Li, Junfeng Tian, Bin Bi, Wei Wang, Weihua Chen, Xianzhe Xu, Fan Wang, Zheng Cao, Zhicheng Zhang, Qiyu Zhang, Ji Zhang, Songfang Huang, Fei Huang, Luo Si, Rong Jin
2021	A*	`conf`	An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives. NeurIPS Qi Qi, Zhishuai Guo, Yi Xu, Rong Jin, Tianbao Yang
2021	J	`jnl`	CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation. CoRR Tongkun Xu, Weihua Chen, Pichao Wang, Fan Wang, Hao Li, Rong Jin
2021	J	`jnl`	CobBO: Coordinate Backoff Bayesian Optimization. CoRR Jian Tan, Niv Nayman, Mengchang Wang, Rong Jin
2021	A*	`conf`	Communication Efficient SGD via Gradient Sampling With Bayes Prior. CVPR Liuyihan Song, Kang Zhao, Pan Pan, Yu Liu, Yingya Zhang, Yinghui Xu, Rong Jin
2021	A*	`conf`	Dash: Semi-Supervised Learning with Dynamic Thresholding. ICML Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yufeng Li, Baigui Sun, Hao Li, Rong Jin
2021	J	`jnl`	Dash: Semi-Supervised Learning with Dynamic Thresholding. CoRR Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yufeng Li, Baigui Sun, Hao Li, Rong Jin
2021	J	`jnl`	Decoupling and Recoupling Spatiotemporal Representation for RGB-D-based Motion Recognition. CoRR Benjia Zhou, Pichao Wang, Jun Wan, Yanyan Liang, Fan Wang, Du Zhang, Zhen Lei, Hao Li, Rong Jin
2021	J	`jnl`	ELSA: Enhanced Local Self-Attention for Vision Transformer. CoRR Jingkai Zhou, Pichao Wang, Fan Wang, Qiong Liu, Hao Li, Rong Jin
2021	J	`jnl`	Effective Model Sparsification by Scheduled Grow-and-Prune Methods. CoRR Xiaolong Ma, Minghai Qin, Fei Sun, Zejiang Hou, Kun Yuan, Yi Xu, Yanzhi Wang, Yen-Kuang Chen, Rong Jin, Yuan Xie
2021	J	`jnl`	Graph Convolution for Re-ranking in Person Re-identification. CoRR Yuqi Zhang, Qian Qi, Chong Liu, Weihua Chen, Fan Wang, Hao Li, Rong Jin
2021	J	`jnl`	IQNAS: Interpretable Integer Quadratic Programming Neural Architecture Search. CoRR Niv Nayman, Yonathan Aflalo, Asaf Noy, Rong Jin, Lihi Zelnik-Manor
2021	J	`jnl`	Improved Fine-tuning by Leveraging Pre-training Data: Theory and Practice. CoRR Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Antoni B. Chan, Rong Jin
2021	J	`jnl`	KVT: k-NN Attention for Boosting Vision Transformers. CoRR Pichao Wang, Xue Wang, Fan Wang, Ming Lin, Shuning Chang, Wen Xie, Hao Li, Rong Jin
2021	J	`jnl`	Large Scale Long-tailed Product Recognition System at Alibaba. CoRR Xiangzeng Zhou, Pan Pan, Yun Zheng, Yinghui Xu, Rong Jin
2021	J	`jnl`	Large-Scale Training System for 100-Million Classification at Alibaba. CoRR Liuyihan Song, Pan Pan, Kang Zhao, Hao Yang, Yiming Chen, Yingya Zhang, Yinghui Xu, Rong Jin
2021	J	`jnl`	Large-Scale Visual Search with Binary Distributed Graph at Alibaba. CoRR Kang Zhao, Pan Pan, Yun Zheng, Yanhao Zhang, Changxu Wang, Yingya Zhang, Yinghui Xu, Rong Jin
2021	A*	`conf`	Learning Accurate Entropy Model with Global Reference for Image Compression. ICLR Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li, Zhenhong Sun, Hao Li, Rong Jin
2021	A*	`conf`	Learning Position and Target Consistency for Memory-Based Video Object Segmentation. CVPR Li Hu, Peng Zhang, Bang Zhang, Pan Pan, Yinghui Xu, Rong Jin
2021	J	`jnl`	Learning Position and Target Consistency for Memory-based Video Object Segmentation. CoRR Li Hu, Peng Zhang, Bang Zhang, Pan Pan, Yinghui Xu, Rong Jin
2021	J	`jnl`	On Stochastic Moving-Average Estimators for Non-Convex Optimization. CoRR Zhishuai Guo, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang
2021	J	`jnl`	On the Convergence of Deep Networks with Sample Quadratic Overparameterization. CoRR Asaf Noy, Yi Xu, Yonathan Aflalo, Rong Jin
2021	J	`jnl`	ParamCrop: Parametric Cubic Cropping for Video Contrastive Learning. CoRR Zhiwu Qing, Ziyuan Huang, Shiwei Zhang, Mingqian Tang, Changxin Gao, Marcelo H. Ang Jr., Rong Jin, Nong Sang
2021	J	`jnl`	Rethinking supervised pre-training for better downstream transferring. CoRR Yutong Feng, Jianwen Jiang, Mingqian Tang, Rong Jin, Yue Gao
2021	J	`jnl`	Revisiting Efficient Object Detection Backbones from Zero-Shot Neural Architecture Search. CoRR Zhenhong Sun, Ming Lin, Xiuyu Sun, Zhiyu Tan, Rong Jin
2021	J	`jnl`	Scaled ReLU Matters for Training Vision Transformers. CoRR Pichao Wang, Xue Wang, Hao Luo, Jingkai Zhou, Zhipeng Zhou, Fan Wang, Hao Li, Rong Jin
2021	A*	`conf`	Self-Supervised Motion Learning From Static Images. CVPR Ziyuan Huang, Shiwei Zhang, Jianwen Jiang, Mingqian Tang, Rong Jin, Marcelo H. Ang
2021	J	`jnl`	Self-Supervised Pre-Training for Transformer-Based Person Re-Identification. CoRR Hao Luo, Pichao Wang, Yi Xu, Feng Ding, Yanxin Zhou, Fan Wang, Hao Li, Rong Jin
2021	A*	`conf`	Self-Supervised Video Representation Learning by Context and Motion Decoupling. CVPR Lianghua Huang, Yu Liu, Bin Wang, Pan Pan, Yinghui Xu, Rong Jin
2021	J	`jnl`	Self-supervised Motion Learning from Static Images. CoRR Ziyuan Huang, Shiwei Zhang, Jianwen Jiang, Mingqian Tang, Rong Jin, Marcelo H. Ang
2021	J	`jnl`	Self-supervised Video Representation Learning by Context and Motion Decoupling. CoRR Lianghua Huang, Yu Liu, Bin Wang, Pan Pan, Yinghui Xu, Rong Jin
2021	J	`jnl`	Shrinking the Upper Confidence Bound: A Dynamic Product Selection Problem for Urban Warehouses. Manag. Sci. Rong Jin, David Simchi-Levi, Li Wang, Xinshang Wang, Sen Yang
2021	A*	`conf`	Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning. AAAI Yu Liu, Lianghua Huang, Pan Pan, Bin Wang, Yinghui Xu, Rong Jin
2021	J	`jnl`	Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning. CoRR Yu Liu, Lianghua Huang, Pan Pan, Bin Wang, Yinghui Xu, Rong Jin
2021	J	`jnl`	TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation. CoRR Zhaoyuan Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li, Rong Jin
2021	J	`jnl`	Unsupervised Visual Representation Learning by Online Constrained K-Means. CoRR Qi Qian, Yuanhong Xu, Juhua Hu, Hao Li, Rong Jin
2021	J	`jnl`	Virtual ID Discovery from E-commerce Media at Alibaba: Exploiting Richness of User Click Behavior for Visual Search Relevance. CoRR Yanhao Zhang, Pan Pan, Yun Zheng, Kang Zhao, Jianmin Wu, Yinghui Xu, Rong Jin
2021	J	`jnl`	Visual Search at Alibaba. CoRR Yanhao Zhang, Pan Pan, Yun Zheng, Kang Zhao, Yingya Zhang, Xiaofeng Ren, Rong Jin
2021	A*	`conf`	Weakly Supervised Representation Learning with Coarse Labels. ICCV Yuanhong Xu, Qi Qian, Hao Li, Rong Jin, Juhua Hu
2021	J	`jnl`	Why Does Multi-Epoch Training Help? CoRR Yi Xu, Qi Qian, Hao Li, Rong Jin
2021	J	`jnl`	Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition. CoRR Ming Lin, Pichao Wang, Zhenhong Sun, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin
2021	A*	`conf`	Zen-NAS: A Zero-Shot NAS for High-Performance Image Recognition. ICCV Ming Lin, Pichao Wang, Zhenhong Sun, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin
2020	—	`conf`	7.2 A 12nm Programmable Convolution-Efficient Neural-Processing-Unit Chip Achieving 825TOPS. ISSCC Yang Jiao, Liang Han, Rong Jin, Yi-Jung Su, Chiente Ho, Li Yin, Yun Li, Long Chen, Zhen Chen, Lu Liu, Zhuyu He, Yu Yan, Jun He, Jun Mao, Xiaotao Zai, Xuejun Wu, Yongquan Zhou, Mingqiu Gu, Guocai Zhu, Rong Zhong, Wenyuan Lee, Ping Chen, Yiping Chen, Weiliang Li, Deyu Xiao, Qing Yan, Mingyuan Zhuang, Jiejun Chen, Yun Tian, Yingzi Lin, Wei Wu, Hao Li, Zesheng Dou
2020	J	`jnl`	A Practical Online Method for Distributionally Deep Robust Optimization. CoRR Qi Qi, Zhishuai Guo, Yi Xu, Rong Jin, Tianbao Yang
2020	J	`jnl`	Attentional Biased Stochastic Gradient for Imbalanced Classification. CoRR Qi Qi, Yi Xu, Rong Jin, Wotao Yin, Tianbao Yang
2020	A*	`conf`	DR Loss: Improving Object Detection by Distributional Ranking. CVPR Qi Qian, Lei Chen, Hao Li, Rong Jin
2020	J	`jnl`	High-dimensional model recovery from random sketched data by exploring intrinsic sparsity. Mach. Learn. Tianbao Yang, Lijun Zhang, Qihang Lin, Shenghuo Zhu, Rong Jin
2020	A	`conf`	Large Scale Long-tailed Product Recognition System at Alibaba. CIKM Xiangzeng Zhou, Pan Pan, Yun Zheng, Yinghui Xu, Rong Jin
2020	A*	`conf`	Large-Scale Training System for 100-Million Classification at Alibaba. KDD Liuyihan Song, Pan Pan, Kang Zhao, Hao Yang, Yiming Chen, Yingya Zhang, Yinghui Xu, Rong Jin
2020	A*	`conf`	Large-scale Multi-modal Search and QA at Alibaba. SIGIR Rong Jin
2020	J	`jnl`	Learning Accurate Entropy Model with Global Reference for Image Compression. CoRR Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li, Zhenhong Sun, Hao Li, Rong Jin
2020	J	`jnl`	Neural Architecture Design for GPU-Efficient Networks. CoRR Ming Lin, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, Rong Jin
2020	A*	`conf`	Price Suggestion for Online Second-hand Items with Texts and Images. ACM Multimedia Liang Han, Zhaozheng Yin, Zhurong Xia, Minqian Tang, Rong Jin
2020	J	`jnl`	Price Suggestion for Online Second-hand Items with Texts and Images. CoRR Liang Han, Zhaozheng Yin, Zhurong Xia, Mingqian Tang, Rong Jin
2020	B	`conf`	Price Suggestion for Online Second-hand Items. ICPR Liang Han, Zhaozheng Yin, Zhurong Xia, Li Guo, Mingqian Tang, Rong Jin
2020	J	`jnl`	Publishing Social Network Graph Eigenspectrum With Privacy Guarantees. IEEE Trans. Netw. Sci. Eng. Faraz Ahmed, Alex X. Liu, Rong Jin
2020	J	`jnl`	Representation Learning with Fine-grained Patterns. CoRR Yuanhong Xu, Qi Qian, Hao Li, Rong Jin, Juhua Hu
2020	J	`jnl`	Towards Understanding Label Smoothing. CoRR Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Rong Jin
2020	J	`jnl`	Vision-based Price Suggestion for Online Second-hand Items. CoRR Liang Han, Zhaozheng Yin, Zhurong Xia, Li Guo, Mingqian Tang, Rong Jin
2020	J	`jnl`	WeMix: How to Better Utilize Data Augmentation. CoRR Yi Xu, Asaf Noy, Ming Lin, Qi Qian, Hao Li, Rong Jin
2019	A*	`conf`	A Practical Semi-Parametric Contextual Bandit. IJCAI Yi Peng, Miao Xie, Jiahao Liu, Xuying Meng, Nan Li, Cheng Yang, Tao Yao, Rong Jin
2019	J	`jnl`	A simple homotopy proximal mapping algorithm for compressive sensing. Mach. Learn. Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou
2019	J	`jnl`	Conservative Exploration for Semi-Bandits with Linear Generalization: A Product Selection Problem for Urban Warehouses. CoRR Rong Jin, David Simchi-Levi, Li Wang, Xinshang Wang, Sen Yang
2019	J	`jnl`	DR Loss: Improving Object Detection by Distributional Ranking. CoRR Qi Qian, Lei Chen, Hao Li, Rong Jin
2019	A	`conf`	Large-Scale Visual Search with Binary Distributed Graph at Alibaba. CIKM Kang Zhao, Pan Pan, Yun Zheng, Yanhao Zhang, Changxu Wang, Yingya Zhang, Yinghui Xu, Rong Jin
2019	A	`conf`	Learning with Non-Convex Truncated Losses by SGD. UAI Yi Xu, Shenghuo Zhu, Sen Yang, Chi Zhang, Rong Jin, Tianbao Yang
2019	—	`conf`	MuffNet: Multi-Layer Feature Federation for Mobile Deep Learning. ICCV Workshops Hesen Chen, Ming Lin, Xiuyu Sun, Qian Qi, Hao Li, Rong Jin
2019	A*	`conf`	Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems. NeurIPS Yi Xu, Rong Jin, Tianbao Yang
2019	A*	`conf`	On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization. ICML Hao Yu, Rong Jin
2019	J	`jnl`	On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization. CoRR Hao Yu, Rong Jin
2019	A*	`conf`	On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Minimization. IJCAI Yi Xu, Zhuoning Yuan, Sen Yang, Rong Jin, Tianbao Yang
2019	A*	`conf`	On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization. ICML Hao Yu, Rong Jin, Sen Yang
2019	J	`jnl`	On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization. CoRR Hao Yu, Rong Jin, Sen Yang
2019	J	`jnl`	Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion. J. Mach. Learn. Res. Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2019	A*	`conf`	Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement. KDD Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin
2019	J	`jnl`	Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement. CoRR Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin
2019	A*	`conf`	Robust Online Matching with User Arrival Distribution Drift. AAAI Yu-Hang Zhou, Chen Liang, Nan Li, Cheng Yang, Shenghuo Zhu, Rong Jin
2019	A*	`conf`	Robust Optimization over Multiple Domains. AAAI Qi Qian, Shenghuo Zhu, Jiasheng Tang, Rong Jin, Baigui Sun, Hao Li
2019	A*	`conf`	Semi-Parametric Sampling for Stochastic Bandits with Many Arms. AAAI Mingdong Ou, Nan Li, Cheng Yang, Shenghuo Zhu, Rong Jin
2019	A*	`conf`	SoftTriple Loss: Deep Metric Learning Without Triplet Sampling. ICCV Qi Qian, Lei Shang, Baigui Sun, Juhua Hu, Tacoma Tacoma, Hao Li, Rong Jin
2019	J	`jnl`	SoftTriple Loss: Deep Metric Learning Without Triplet Sampling. CoRR Qi Qian, Lei Shang, Baigui Sun, Juhua Hu, Hao Li, Rong Jin
2019	A*	`conf`	Stagewise Training Accelerates Convergence of Testing Error Over SGD. NeurIPS Zhuoning Yuan, Yan Yan, Rong Jin, Tianbao Yang
2019	A*	`conf`	Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence. ICML Yi Xu, Qi Qi, Qihang Lin, Rong Jin, Tianbao Yang
2019	A	`conf`	Virtual ID Discovery from E-commerce Media at Alibaba: Exploiting Richness of User Click Behavior for Visual Search Relevance. CIKM Yanhao Zhang, Pan Pan, Yun Zheng, Kang Zhao, Jianmin Wu, Yinghui Xu, Rong Jin
2019	A*	`conf`	Vision-based Price Suggestion for Online Second-hand Items. ACM Multimedia Liang Han, Zhaozheng Yin, Zhurong Xia, Li Guo, Mingqian Tang, Rong Jin
2019	A*	`conf`	Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee. AAAI Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin
2019	J	`jnl`	Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee. CoRR Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin
2019	A*	`conf`	XNAS: Neural Architecture Search with Expert Advice. NeurIPS Niv Nayman, Asaf Noy, Tal Ridnik, Itamar Friedman, Rong Jin, Lihi Zelnik-Manor
2019	J	`jnl`	XNAS: Neural Architecture Search with Expert Advice. CoRR Niv Nayman, Asaf Noy, Tal Ridnik, Itamar Friedman, Rong Jin, Lihi Zelnik-Manor
2018	—	`ch.`	Combining Link and Content for Community Detection. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu
2018	A*	`conf`	Dynamic Regret of Strongly Adaptive Methods. ICML Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2018	A*	`conf`	Extremely Low Bit Neural Network: Squeeze the Last Bit Out With ADMM. AAAI Cong Leng, Zesheng Dou, Hao Li, Shenghuo Zhu, Rong Jin
2018	A*	`conf`	Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions. NeurIPS Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Rong Jin, Tianbao Yang
2018	J	`jnl`	Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions. CoRR Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Rong Jin, Tianbao Yang
2018	A*	`conf`	First-order Stochastic Algorithms for Escaping From Saddle Points in Almost Linear Time. NeurIPS Yi Xu, Rong Jin, Tianbao Yang
2018	A*	`conf`	Large-Scale Distance Metric Learning With Uncertainty. CVPR Qi Qian, Jiasheng Tang, Hao Li, Shenghuo Zhu, Rong Jin
2018	J	`jnl`	Large-scale Distance Metric Learning with Uncertainty. CoRR Qi Qian, Jiasheng Tang, Hao Li, Shenghuo Zhu, Rong Jin
2018	J	`jnl`	Learning with Non-Convex Truncated Losses by SGD. CoRR Yi Xu, Shenghuo Zhu, Sen Yang, Chi Zhang, Rong Jin, Tianbao Yang
2018	A*	`conf`	Multinomial Logit Bandit with Linear Utility Functions. IJCAI Mingdong Ou, Nan Li, Shenghuo Zhu, Rong Jin
2018	J	`jnl`	Multinomial Logit Bandit with Linear Utility Functions. CoRR Mingdong Ou, Nan Li, Shenghuo Zhu, Rong Jin
2018	J	`jnl`	Robust Optimization over Multiple Domains. CoRR Qi Qian, Shenghuo Zhu, Jiasheng Tang, Rong Jin, Baigui Sun, Hao Li
2018	—	`conf`	Seamless Color Mapping for 3D Reconstruction with Consumer-Grade Scanning Devices. ECCV Workshops (1) Bin Wang, Pan Pan, Qinjie Xiao, Likang Luo, Xiaofeng Ren, Rong Jin, Xiaogang Jin
2018	A*	`conf`	Visual Search at Alibaba. KDD Yanhao Zhang, Pan Pan, Yun Zheng, Kang Zhao, Yingya Zhang, Xiaofeng Ren, Rong Jin
2018	J	`jnl`	Why Does Stagewise Training Accelerate Convergence of Testing Error Over SGD? CoRR Tianbao Yang, Yan Yan, Zhuoning Yuan, Rong Jin
2017	A*	`conf`	A Two-Stage Approach for Learning a Sparse Model with Sharp Excess Risk Analysis. AAAI Zhe Li, Tianbao Yang, Lijun Zhang, Rong Jin
2017	A*	`conf`	Deep Learning at Alibaba. IJCAI Rong Jin
2017	A*	`conf`	Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-type of Risk Bounds. COLT Lijun Zhang, Tianbao Yang, Rong Jin
2017	J	`jnl`	Empirical Risk Minimization for Stochastic Convex Optimization: O(1/n)- and O(1/n CoRR Lijun Zhang, Tianbao Yang, Rong Jin
2017	J	`jnl`	Extremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM. CoRR Cong Leng, Hao Li, Shenghuo Zhu, Rong Jin
2017	J	`jnl`	Finding multiple stable clusterings. Knowl. Inf. Syst. Juhua Hu, Qi Qian, Jian Pei, Rong Jin, Shenghuo Zhu
2017	—	`conf`	Improved Dynamic Regret for Non-degenerate Functions. NIPS Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou
2017	A*	`conf`	Missing Modalities Imputation via Cascaded Residual Autoencoder. CVPR Luan Tran, Xiaoming Liu, Jiayu Zhou, Rong Jin
2017	J	`jnl`	Sparse Learning with Stochastic Composite Optimization. IEEE Trans. Pattern Anal. Mach. Intell. Weizhong Zhang, Lijun Zhang, Zhongming Jin, Rong Jin, Deng Cai, Xuelong Li, Ronghua Liang, Xiaofei He
2017	J	`jnl`	Strongly Adaptive Regret Implies Optimally Dynamic Regret. CoRR Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2017	A	`conf`	The Opensesame NIST 2016 Speaker Recognition Evaluation System. INTERSPEECH Gang Liu, Qi Qian, Zhibin Wang, Qingen Zhao, Tianzhou Wang, Hao Li, Jian Xue, Shenghuo Zhu, Rong Jin, Tuo Zhao
2016	A*	`conf`	Accelerated Sparse Linear Regression via Random Projection. AAAI Weizhong Zhang, Lijun Zhang, Rong Jin, Deng Cai, Xiaofei He
2016	A*	`conf`	Fast and Accurate Refined Nyström-Based Kernel SVM. AAAI Zhe Li, Tianbao Yang, Lijun Zhang, Rong Jin
2016	J	`jnl`	Improved dynamic regret for non-degeneracy functions. CoRR Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou
2016	A	`conf`	Large-scale Robust Online Matching and Its Application in E-commerce. CIKM Rong Jin
2016	J	`jnl`	On Data Preconditioning for Regularized Loss Minimization. Mach. Learn. Tianbao Yang, Rong Jin, Shenghuo Zhu, Qihang Lin
2016	J	`jnl`	One-pass AUC optimization. Artif. Intell. Wei Gao, Lu Wang, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou
2016	A*	`conf`	Online Stochastic Linear Optimization under One-bit Feedback. ICML Lijun Zhang, Tianbao Yang, Rong Jin, Yichi Xiao, Zhi-Hua Zhou
2016	J	`jnl`	Online kernel learning with nearly constant support vectors. Neurocomputing Ming Lin, Lijun Zhang, Rong Jin, Shifeng Weng, Changshui Zhang
2016	A	`conf`	Social Graph Publishing with Privacy Guarantees. ICDCS Faraz Ahmed, Alex X. Liu, Rong Jin
2016	B	`conf`	Sparse Learning for Large-Scale and High-Dimensional Data: A Randomized Convex-Concave Optimization Approach. ALT Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2016	A*	`conf`	Stochastic Optimization for Kernel PCA. AAAI Lijun Zhang, Tianbao Yang, Jinfeng Yi, Rong Jin, Zhi-Hua Zhou
2016	A*	`conf`	Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient. ICML Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi
2016	J	`jnl`	Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient. CoRR Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi
2015	A	`conf`	A Simple Homotopy Algorithm for Compressive Sensing. AISTATS Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2015	A*	`conf`	An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection. ICML Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu
2015	J	`jnl`	An efficient primal dual prox method for non-smooth optimization. Mach. Learn. Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Shenghuo Zhu
2015	J	`jnl`	Analysis of Nuclear Norm Regularization for Full-rank Matrix Completion. CoRR Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2015	A*	`conf`	Big Data Analytics: Optimization and Randomization. KDD Tianbao Yang, Qihang Lin, Rong Jin
2015	A*	`conf`	CUR Algorithm for Partially Observed Matrices. ICML Miao Xu, Rong Jin, Zhi-Hua Zhou
2015	J	`jnl`	Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD). Mach. Learn. Qi Qian, Rong Jin, Jinfeng Yi, Lijun Zhang, Shenghuo Zhu
2015	J	`jnl`	Fast Sparse Least-Squares Regression with Non-Asymptotic Guarantees. CoRR Tianbao Yang, Lijun Zhang, Qihang Lin, Rong Jin
2015	A*	`conf`	Finding Multiple Stable Clusterings. ICDM Juhua Hu, Qi Qian, Jian Pei, Rong Jin, Shenghuo Zhu
2015	A*	`conf`	Fine-grained visual categorization via multi-stage metric learning. CVPR Qi Qian, Rong Jin, Shenghuo Zhu, Yuanqing Lin
2015	J	`jnl`	Learning to Rank Image Tags With Limited Training Examples. IEEE Trans. Image Process. Songhe Feng, Zheyun Feng, Rong Jin
2015	A*	`conf`	Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization. COLT Mehrdad Mahdavi, Lijun Zhang, Rong Jin
2015	A*	`conf`	Nystrom Approximation for Sparse Kernel Methods: Theoretical Analysis and Empirical Evaluation. AAAI Zenglin Xu, Rong Jin, Bin Shen, Shenghuo Zhu
2015	A*	`conf`	Online Bandit Learning for a Special Class of Non-Convex Losses. AAAI Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2015	J	`jnl`	Online Stochastic Linear Optimization under One-bit Feedback. CoRR Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2015	J	`jnl`	Similarity Learning via Adaptive Regression and Its Application to Image Retrieval. CoRR Qi Qian, Inci M. Baytas, Rong Jin, Anil K. Jain, Shenghuo Zhu
2015	—	`conf`	Sparse Kernel Clustering of Massive High-Dimensional Data sets with Large Number of Clusters. PIKM@CIKM Radha Chitta, Anil K. Jain, Rong Jin
2015	J	`jnl`	Sparse Learning for Large-scale and High-dimensional Data: A Randomized Convex-concave Optimization Approach. CoRR Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2015	J	`jnl`	Stochastic Proximal Gradient Descent for Nuclear Norm Regularization. CoRR Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou
2015	A*	`conf`	Stock Constrained Recommendation in Tmall. KDD Wenliang Zhong, Rong Jin, Cheng Yang, Xiaowei Yan, Qi Zhang, Qiang Li
2015	—	`conf`	Stream Clustering: Efficient Kernel-Based Approximation Using Importance Sampling. ICDM Workshops Radha Chitta, Rong Jin, Anil K. Jain
2015	A*	`conf`	Theory of Dual-sparse Regularized Randomized Reduction. ICML Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu
2015	J	`jnl`	Theory of Dual-sparse Regularized Randomized Reduction. CoRR Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu
2015	A	`conf`	Topic Modeling in Semantic Space with Keywords. CIKM Xiaojia Pu, Rong Jin, Gangshan Wu, Dingyi Han, Gui-Rong Xue
2015	J	`jnl`	Towards Making High Dimensional Distance Metric Learning Practical. CoRR Qi Qian, Rong Jin, Lijun Zhang, Shenghuo Zhu
2014	J	`jnl`	A Simple Homotopy Proximal Mapping for Compressive Sensing. CoRR Tianbao Yang, Lijun Zhang, Rong Jin, Shenghuo Zhu
2014	A*	`conf`	A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data. ICML Jinfeng Yi, Lijun Zhang, Jun Wang, Rong Jin, Anil K. Jain
2014	J	`jnl`	Active Learning by Querying Informative and Representative Examples. IEEE Trans. Pattern Anal. Mach. Intell. Sheng-Jun Huang, Rong Jin, Zhi-Hua Zhou
2014	J	`jnl`	An Integrated Framework for High Dimensional Distance Metric Learning and Its Application to Fine-Grained Visual Categorization. CoRR Qi Qian, Rong Jin, Shenghuo Zhu, Yuanqing Lin
2014	J	`jnl`	Binary Excess Risk for Smooth Convex Surrogates. CoRR Mehrdad Mahdavi, Lijun Zhang, Rong Jin
2014	J	`jnl`	CUR Algorithm for Partially Observed Matrices. CoRR Miao Xu, Rong Jin, Zhi-Hua Zhou
2014	J	`jnl`	CUR Algorithm with Incomplete Matrix Observation. CoRR Rong Jin, Shenghuo Zhu
2014	—	`ch.`	Combining Link and Content for Community Detection. Encyclopedia of Social Network Analysis and Mining Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu
2014	A*	`conf`	Distance metric learning using dropout: a structured regularization approach. KDD Qi Qian, Juhua Hu, Rong Jin, Jian Pei, Shenghuo Zhu
2014	A*	`conf`	Efficient Algorithms for Robust One-bit Compressive Sensing. ICML Lijun Zhang, Jinfeng Yi, Rong Jin
2014	A	`conf`	Efficient Sparse Recovery via Adaptive Non-Convex Regularizers with Oracle Property. UAI Ming Lin, Rong Jin, Changshui Zhang
2014	J	`jnl`	Excess Risk Bounds for Exponentially Concave Losses. CoRR Mehrdad Mahdavi, Rong Jin
2014	—	`conf`	Extracting Certainty from Uncertainty: Transductive Pairwise Classification from Pairwise Similarities. NIPS Tianbao Yang, Rong Jin
2014	—	`conf`	Image Tag Completion by Noisy Matrix Recovery. ECCV (7) Zheyun Feng, Songhe Feng, Rong Jin, Anil K. Jain
2014	J	`jnl`	Multiple Kernel Learning for Visual Object Recognition: A Review. IEEE Trans. Pattern Anal. Mach. Intell. Serhat Selcuk Bucak, Rong Jin, Anil K. Jain
2014	J	`jnl`	On Data Preconditioning for Regularized Loss Minimization. CoRR Tianbao Yang, Rong Jin, Shenghuo Zhu, Qihang Lin
2014	J	`jnl`	Online Feature Selection and Its Applications. IEEE Trans. Knowl. Data Eng. Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Rong Jin
2014	J	`jnl`	Online Multiple Kernel Similarity Learning for Visual Search. IEEE Trans. Pattern Anal. Mach. Intell. Hao Xia, Steven C. H. Hoi, Rong Jin, Peilin Zhao
2014	A*	`conf`	Privacy and Regression Model Preserved Learning. AAAI Jinfeng Yi, Jun Wang, Rong Jin
2014	J	`jnl`	Random Projections for Classification: A Recovery Approach. IEEE Trans. Inf. Theory Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang, Shenghuo Zhu
2014	J	`jnl`	Regret bounded by gradual variation for online convex optimization. Mach. Learn. Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Shenghuo Zhu
2014	J	`jnl`	Scalable Kernel Clustering: Approximate Kernel k-means. CoRR Radha Chitta, Rong Jin, Timothy C. Havens, Anil K. Jain
2014	A*	`conf`	Sparse Learning for Stochastic Composite Optimization. AAAI Weizhong Zhang, Lijun Zhang, Yao Hu, Rong Jin, Deng Cai, Xiaofei He
2014	—	`conf`	Top Rank Optimization in Linear Time. NIPS Nan Li, Rong Jin, Zhi-Hua Zhou
2014	J	`jnl`	Top Rank Optimization in Linear Time. CoRR Nan Li, Rong Jin, Zhi-Hua Zhou
2013	J	`jnl`	A New Analysis of Compressive Sensing by Stochastic Proximal Gradient Descent CoRR Rong Jin, Tianbao Yang, Shenghuo Zhu
2013	J	`jnl`	A Random Matrix Approach to Differential Privacy and Structure Preserved Social Network Graph Publishing. CoRR Faraz Ahmed, Rong Jin, Alex X. Liu
2013	A*	`conf`	Compressed Hashing. CVPR Yue Lin, Rong Jin, Deng Cai, Shuicheng Yan, Xuelong Li
2013	J	`jnl`	Efficient Distance Metric Learning by Adaptive Sampling and Mini-Batch Stochastic Gradient Descent (SGD) CoRR Qi Qian, Rong Jin, Jinfeng Yi, Lijun Zhang, Shenghuo Zhu
2013	J	`jnl`	Improved Bounds for the Nyström Method With Application to Kernel Classification. IEEE Trans. Inf. Theory Rong Jin, Tianbao Yang, Mehrdad Mahdavi, Yufeng Li, Zhi-Hua Zhou
2013	J	`jnl`	Improving the Minimax Rate of Active Learning. CoRR Lijun Zhang, Mehrdad Mahdavi, Rong Jin
2013	B	`conf`	Inferring Users' Preferences from Crowdsourced Pairwise Comparisons: A Matrix Completion Approach. HCOMP Jinfeng Yi, Rong Jin, Shaili Jain, Anil K. Jain
2013	A*	`conf`	Large-Scale Image Annotation by Efficient and Robust Kernel Metric Learning. ICCV Zheyun Feng, Rong Jin, Anil K. Jain
2013	—	`conf`	Linear Convergence with Condition Number Independent Access of Full Gradients. NIPS Lijun Zhang, Mehrdad Mahdavi, Rong Jin
2013	—	`conf`	Mixed Optimization for Smooth Functions. NIPS Mehrdad Mahdavi, Lijun Zhang, Rong Jin
2013	J	`jnl`	MixedGrad: An O(1/T) Convergence Rate Algorithm for Stochastic Smooth Optimization. CoRR Mehrdad Mahdavi, Rong Jin
2013	J	`jnl`	O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions CoRR Lijun Zhang, Tianbao Yang, Rong Jin, Xiaofei He
2013	—	`conf`	O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions. ICML (3) Lijun Zhang, Tianbao Yang, Rong Jin, Xiaofei He
2013	J	`jnl`	On Theoretical Analysis of Distributed Stochastic Dual Coordinate Ascent. CoRR Tianbao Yang, Shenghuo Zhu, Rong Jin, Yuanqing Lin
2013	J	`jnl`	One-Pass AUC Optimization CoRR Wei Gao, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou
2013	—	`conf`	One-Pass AUC Optimization. ICML (3) Wei Gao, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou
2013	—	`conf`	Online Kernel Learning with a Near Optimal Sparsity Bound. ICML (3) Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He
2013	J	`jnl`	Online Multiple Kernel Classification. Mach. Learn. Steven C. H. Hoi, Rong Jin, Peilin Zhao, Tianbao Yang
2013	J	`jnl`	Passive Learning with Target Risk CoRR Mehrdad Mahdavi, Rong Jin
2013	A*	`conf`	Passive Learning with Target Risk. COLT Mehrdad Mahdavi, Rong Jin
2013	A*	`conf`	Recovering the Optimal Solution by Dual Random Projection. COLT Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang, Shenghuo Zhu
2013	—	`conf`	Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion. ICML (3) Jinfeng Yi, Lijun Zhang, Rong Jin, Qi Qian, Anil K. Jain
2013	J	`jnl`	Sparse Multiple Kernel Learning with Geometric Convergence Rate CoRR Rong Jin, Tianbao Yang, Mehrdad Mahdavi
2013	—	`conf`	Speedup Matrix Completion with Side Information: Application to Multi-Label Learning. NIPS Miao Xu, Rong Jin, Zhi-Hua Zhou
2013	—	`conf`	Stochastic Convex Optimization with Multiple Objectives. NIPS Mehrdad Mahdavi, Tianbao Yang, Rong Jin
2013	J	`jnl`	Stochastic Optimization of Smooth Loss. CoRR Rong Jin
2013	J	`jnl`	Tag Completion for Image Retrieval. IEEE Trans. Pattern Anal. Mach. Intell. Lei Wu, Rong Jin, Anil K. Jain
2012	J	`jnl`	A Bayesian Approach toward Active Learning for Collaborative Filtering CoRR Rong Jin, Luo Si
2012	J	`jnl`	A Bayesian Framework for Community Detection Integrating Content and Link CoRR Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu
2012	J	`jnl`	A Kernel Approach to Multi-Task Learning with Task-Specific Kernels. J. Comput. Sci. Technol. Wei Wu, Hang Li, Yunhua Hu, Rong Jin
2012	A*	`conf`	A Simple Algorithm for Semi-supervised Learning with Improved Generalization Error Bound. ICML Ming Ji, Tianbao Yang, Binbin Lin, Rong Jin, Jiawei Han
2012	J	`jnl`	An Efficient Primal-Dual Prox Method for Non-Smooth Optimization CoRR Tianbao Yang, Rong Jin, Mehrdad Mahdavi, Shenghuo Zhu
2012	J	`jnl`	An Improved Bound for the Nystrom Method for Large Eigengap CoRR Mehrdad Mahdavi, Tianbao Yang, Rong Jin
2012	J	`jnl`	Bayesian Active Distance Metric Learning CoRR Liu Yang, Rong Jin, Rahul Sukthankar
2012	A*	`conf`	Boosting multi-kernel locality-sensitive hashing for scalable image retrieval. SIGIR Hao Xia, Pengcheng Wu, Steven C. H. Hoi, Rong Jin
2012	—	`conf`	Crowdclustering with Sparse Pairwise Labels: A Matrix Completion Approach. HCOMP@AAAI Jinfeng Yi, Rong Jin, Anil K. Jain, Shaili Jain
2012	J	`jnl`	Efficient Constrained Regret Minimization CoRR Mehrdad Mahdavi, Tianbao Yang, Rong Jin
2012	A*	`conf`	Efficient Kernel Clustering Using Random Fourier Features. ICDM Radha Chitta, Rong Jin, Anil K. Jain
2012	A*	`conf`	Efficient Online Learning for Large-Scale Sparse Kernel Logistic Regression. AAAI Lijun Zhang, Rong Jin, Chun Chen, Jiajun Bu, Xiaofei He
2012	J	`jnl`	Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning CoRR Peilin Zhao, Jialei Wang, Pengcheng Wu, Rong Jin, Steven C. H. Hoi
2012	A*	`conf`	Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning. ICML Steven C. H. Hoi, Jialei Wang, Peilin Zhao, Rong Jin, Pengcheng Wu
2012	J	`jnl`	Image Retrieval in Forensics: Tattoo Image Database Application. IEEE Multim. Jung-Eun Lee, Rong Jin, Anil K. Jain, Wei Tong
2012	J	`jnl`	Introduction to the Special Section on Distance Metric Learning in Intelligent Systems. ACM Trans. Intell. Syst. Technol. Steven C. H. Hoi, Rong Jin, Jinhui Tang, Zhi-Hua Zhou
2012	J	`jnl`	Large-scale near-duplicate image retrieval by kernel density estimation. Int. J. Multim. Inf. Retr. Wei Tong, Fengjie Li, Rong Jin, Anil K. Jain
2012	J	`jnl`	Learning Bregman Distance Functions for Semi-Supervised Clustering. IEEE Trans. Knowl. Data Eng. Lei Wu, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Nenghai Yu
2012	—	`conf`	Learning kernel combination from noisy pairwise constraints. SSP Tianbao Yang, Rong Jin, Anil K. Jain
2012	J	`jnl`	Multiple Kernel Learning from Noisy Labels by Stochastic Programming CoRR Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou
2012	A*	`conf`	Multiple Kernel Learning from Noisy Labels by Stochastic Programming. ICML Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou
2012	—	`conf`	Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison. NIPS Tianbao Yang, Yufeng Li, Mehrdad Mahdavi, Rong Jin, Zhi-Hua Zhou
2012	A*	`conf`	Online Kernel Selection: Algorithms and Evaluations. AAAI Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Yi, Steven C. H. Hoi
2012	A*	`conf`	Online Optimization with Gradual Variations. COLT Chao-Kai Chiang, Tianbao Yang, Chia-Jung Lee, Mehrdad Mahdavi, Chi-Jen Lu, Rong Jin, Shenghuo Zhu
2012	J	`jnl`	Online Stochastic Optimization with Multiple Objectives CoRR Mehrdad Mahdavi, Tianbao Yang, Rong Jin
2012	—	`conf`	Online feature selection for mining big data. BigMine Steven C. H. Hoi, Jialei Wang, Peilin Zhao, Rong Jin
2012	J	`jnl`	Preference-based Graphic Models for Collaborative Filtering CoRR Rong Jin, Luo Si, ChengXiang Zhai
2012	A*	`conf`	Random Projection with Filtering for Nearly Duplicate Search. AAAI Yue Lin, Rong Jin, Deng Cai, Xiaofei He
2012	J	`jnl`	Recovering Optimal Solution by Dual Random Projection CoRR Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang
2012	A*	`conf`	Robust Ensemble Clustering by Matrix Completion. ICDM Jinfeng Yi, Tianbao Yang, Rong Jin, Anil K. Jain, Mehrdad Mahdavi
2012	J	`jnl`	Robust Metric Learning by Smooth Optimization CoRR Kaizhu Huang, Rong Jin, Zenglin Xu, Cheng-Lin Liu
2012	—	`conf`	Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning. NIPS Jinfeng Yi, Rong Jin, Anil K. Jain, Shaili Jain, Tianbao Yang
2012	—	`conf`	Stochastic Gradient Descent with Only One Projection. NIPS Mehrdad Mahdavi, Tianbao Yang, Rong Jin, Shenghuo Zhu, Jinfeng Yi
2012	J	`jnl`	Tattoo Image Matching and Retrieval. Computer Anil K. Jain, Rong Jin, Jung-Eun Lee
2012	J	`jnl`	Trading regret for efficiency: online convex optimization with long term constraints. J. Mach. Learn. Res. Mehrdad Mahdavi, Rong Jin, Tianbao Yang
2012	—	`conf`	Wearable autonomous microsystem with electrochemical gas sensor array for real-time health and safety monitoring. EMBC Haitao Li, Xiaoyi Mu, Zhe Wang, Xiaowen Liu, Min Guo, Rong Jin, Xiangqun Zeng, Andrew J. Mason
2011	B	`conf`	A kernel density based approach for large scale image retrieval. ICMR Wei Tong, Fengjie Li, Tianbao Yang, Rong Jin, Anil K. Jain
2011	A*	`conf`	A probabilistic representation for efficient large scale visual recognition tasks. CVPR Subhabrata Bhattacharya, Rahul Sukthankar, Rong Jin, Mubarak Shah
2011	J	`jnl`	Active multiple kernel learning for interactive 3D object retrieval systems. ACM Trans. Interact. Intell. Syst. Steven C. H. Hoi, Rong Jin
2011	A*	`conf`	Approximate kernel k-means: solution to large scale kernel clustering. KDD Radha Chitta, Rong Jin, Timothy C. Havens, Anil K. Jain
2011	J	`jnl`	Detecting communities and their evolutions in dynamic social networks - a Bayesian approach. Mach. Learn. Tianbao Yang, Yun Chi, Shenghuo Zhu, Yihong Gong, Rong Jin
2011	J	`jnl`	Distance metric learning from uncertain side information for automated photo tagging. ACM Trans. Intell. Syst. Technol. Lei Wu, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Nenghai Yu
2011	J	`jnl`	Double Updating Online Learning. J. Mach. Learn. Res. Peilin Zhao, Steven C. H. Hoi, Rong Jin
2011	J	`jnl`	Improved Bound for the Nystrom's Method and its Application to Kernel Classification CoRR Rong Jin, Tianbao Yang, Mehrdad Mahdavi
2011	A*	`conf`	Learning to trade off between exploration and exploitation in multiclass bandit prediction. KDD Hamed Valizadegan, Rong Jin, Shijun Wang
2011	A*	`conf`	Machine learning for information retrieval. SIGIR Luo Si, Rong Jin
2011	A*	`conf`	Multi-Task Learning in Square Integrable Space. AAAI Wei Wu, Hang Li, Yunhua Hu, Rong Jin
2011	A*	`conf`	Multi-label learning with incomplete class assignments. CVPR Serhat Selcuk Bucak, Rong Jin, Anil K. Jain
2011	A*	`conf`	Online AUC Maximization. ICML Peilin Zhao, Steven C. H. Hoi, Rong Jin, Tianbao Yang
2011	J	`jnl`	Regret Bound by Variation for Online Convex Optimization CoRR Tianbao Yang, Rong Jin, Mehrdad Mahdavi
2011	—	`book`	Social Media Modeling and Computing. Steven C. H. Hoi, Jiebo Luo, Susanne Boll, Dong Xu, Rong Jin
2011	B	`conf`	Speedup of fuzzy and possibilistic kernel c-means for large-scale clustering. FUZZ-IEEE Timothy C. Havens, Radha Chitta, Anil K. Jain, Rong Jin
2011	J	`jnl`	Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints CoRR Mehrdad Mahdavi, Rong Jin, Tianbao Yang
2010	J	`jnl`	A Boosting Framework for Visuality-Preserving Distance Metric Learning and Its Application to Medical Image Retrieval. IEEE Trans. Pattern Anal. Mach. Intell. Liu Yang, Rong Jin, Lily B. Mummert, Rahul Sukthankar, Adam Goode, Bin Zheng, Steven C. H. Hoi, Mahadev Satyanarayanan
2010	A	`conf`	A Potential-based Framework for Online Multi-class Learning with Partial Feedback. AISTATS Shijun Wang, Rong Jin, Hamed Valizadegan
2010	—	`conf`	Active Learning by Querying Informative and Representative Examples. NIPS Sheng-Jun Huang, Rong Jin, Zhi-Hua Zhou
2010	A	`conf`	Directed Network Community Detection: A Popularity and Productivity Link Model. SDM Tianbao Yang, Yun Chi, Shenghuo Zhu, Yihong Gong, Rong Jin
2010	J	`jnl`	Discriminative semi-supervised feature selection via manifold regularization. IEEE Trans. Neural Networks Zenglin Xu, Irwin King, Michael R. Lyu, Rong Jin
2010	J	`jnl`	Efficient Algorithm for Localized Support Vector Machine. IEEE Trans. Knowl. Data Eng. Haibin Cheng, Pang-Ning Tan, Rong Jin
2010	A	`conf`	Exclusive Lasso for Multi-task Feature Selection. AISTATS Yang Zhou, Rong Jin, Steven C. H. Hoi
2010	A*	`conf`	Exploitation and exploration in a performance based contextual advertising system. KDD Wei Li, Xuerui Wang, Ruofei Zhang, Ying Cui, Jianchang Mao, Rong Jin
2010	A*	`conf`	Learning from Noisy Side Information by Generalized Maximum Entropy Model. ICML Tianbao Yang, Rong Jin, Anil K. Jain
2010	—	`conf`	Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition. NIPS Serhat Selcuk Bucak, Rong Jin, Anil K. Jain
2010	—	`conf`	Non-parametric Mixture Models for Clustering. SSPR/SPR Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain
2010	J	`jnl`	On the Use of Dynamic Bayesian Networks in Reconstructing Functional Neuronal Networks from Spike Train Ensembles. Neural Comput. Seif Eldawlatly, Yang Zhou, Rong Jin, Karim G. Oweiss
2010	B	`conf`	Online Multiple Kernel Learning: Algorithms and Mistake Bounds. ALT Rong Jin, Steven C. H. Hoi, Tianbao Yang
2010	A*	`conf`	Online visual vocabulary pruning using pairwise constraints. CVPR Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain
2010	—	`ed.`	Proceedings of second ACM SIGMM workshop on Social media, WSM@MM 2010, Firenze, Italy, October 25, 2010 WSM@MM Susanne Boll, Steven C. H. Hoi, Jiebo Luo, Roelof van Zwol, Rong Jin, Irwin King, Yiannis Kompatsiaris, Dong Xu
2010	A	`conf`	Robust Metric Learning by Smooth Optimization. UAI Kaizhu Huang, Rong Jin, Zenglin Xu, Cheng-Lin Liu
2010	A*	`conf`	Simple and Efficient Multiple Kernel Learning by Group Lasso. ICML Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King, Michael R. Lyu
2010	A*	`conf`	Smooth Optimization for Effective Multiple Kernel Learning. AAAI Zenglin Xu, Rong Jin, Shenghuo Zhu, Michael R. Lyu, Irwin King
2010	J	`jnl`	Understanding bag-of-words model: a statistical framework. Int. J. Mach. Learn. Cybern. Yin Zhang, Rong Jin, Zhi-Hua Zhou
2010	B	`conf`	Unsupervised Ensemble Ranking: Application to Large-Scale Image Retrieval. ICPR Jung-Eun Lee, Rong Jin, Anil K. Jain
2010	A*	`conf`	Unsupervised transfer classification: application to text categorization. KDD Tianbao Yang, Rong Jin, Anil K. Jain, Yang Zhou, Wei Tong
2009	A	`conf`	A Bayesian Approach Toward Finding Communities and Their Evolutions in Dynamic Social Networks. SDM Tianbao Yang, Yun Chi, Shenghuo Zhu, Yihong Gong, Rong Jin
2009	A	`conf`	A Bayesian Framework for Community Detection Integrating Content and Link. UAI Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu
2009	—	`conf`	Adaptive Regularization for Transductive Support Vector Machine. NIPS Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael R. Lyu, Zhirong Yang
2009	A	`conf`	An Information Geometry Approach for Distance Metric Learning. AISTATS Shijun Wang, Rong Jin
2009	—	`conf`	An efficient key point quantization algorithm for large scale image retrieval. LS-MMRM@ACM Multimedia Fengjie Li, Wei Tong, Rong Jin, Anil K. Jain, Jung-Eun Lee
2009	J	`jnl`	Batch Mode Active Learning with Applications to Text Categorization and Image Retrieval. IEEE Trans. Knowl. Data Eng. Steven C. H. Hoi, Rong Jin, Michael R. Lyu
2009	A*	`conf`	Combining link and content for community detection: a discriminative approach. KDD Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu
2009	B	`conf`	Content-based image retrieval: An application to tattoo images. ICIP Anil K. Jain, Jung-Eun Lee, Rong Jin, Nicholas Gregg
2009	—	`conf`	DUOL: A Double Updating Approach for Online Learning. NIPS Peilin Zhao, Steven C. H. Hoi, Rong Jin
2009	A*	`conf`	Discriminative Semi-Supervised Feature Selection via Manifold Regularization. IJCAI Zenglin Xu, Rong Jin, Michael R. Lyu, Irwin King
2009	A*	`conf`	Distance metric learning from uncertain side information with application to automated photo tagging. ACM Multimedia Lei Wu, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Nenghai Yu
2009	A*	`conf`	Efficient multi-label ranking for multi-class learning: Application to object recognition. ICCV Serhat Selcuk Bucak, Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain
2009	A*	`conf`	First ACM SIGMM international workshop onsocial media (WSM'09). ACM Multimedia Susanne Boll, Steven C. H. Hoi, Jiebo Luo, Rong Jin, Irwin King, Dong Xu
2009	—	`conf`	Graffiti-ID: matching and retrieval of graffiti images. MiFor@MM Anil K. Jain, Jung-Eun Lee, Rong Jin
2009	J	`jnl`	Identifying Functional Connectivity in Large-Scale Neural Ensemble Recordings: A Multiscale Data Mining Approach. Neural Comput. Seif Eldawlatly, Rong Jin, Karim G. Oweiss
2009	Misc	`conf`	Inferring functional cortical networks from spike train ensembles using Dynamic Bayesian Networks. ICASSP Seif Eldawlatly, Yang Zhou, Rong Jin, Karim G. Oweiss
2009	—	`conf`	Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering. NIPS Lei Wu, Rong Jin, Steven C. H. Hoi, Jianke Zhu, Nenghai Yu
2009	A*	`conf`	Learning a distance metric from multi-instance multi-label data. CVPR Rong Jin, Shijun Wang, Zhi-Hua Zhou
2009	—	`conf`	Learning to Rank by Optimizing NDCG Measure. NIPS Hamed Valizadegan, Rong Jin, Ruofei Zhang, Jianchang Mao
2009	A*	`conf`	Non-monotonic feature selection. ICML Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, Irwin King
2009	A*	`conf`	Online learning by ellipsoid method. ICML Liu Yang, Rong Jin, Jieping Ye
2009	—	`ed.`	Proceedings of the first SIGMM workshop on Social media, WSM@MM 2009, Beijing, China, October 23, 2009 WSM@MM Susanne Boll, Steven C. H. Hoi, Jiebo Luo, Rong Jin, Irwin King, Dong Xu
2009	J	`jnl`	Reconstruct modular phenotype-specific gene networks by knowledge-driven matrix factorization. Bioinform. Xuerui Yang, Yang Zhou, Rong Jin, Christina Chan
2009	—	`conf`	Regularized Distance Metric Learning: Theory and Algorithm. NIPS Rong Jin, Shijun Wang, Yang Zhou
2009	J	`jnl`	SemiBoost: Boosting for Semi-Supervised Learning. IEEE Trans. Pattern Anal. Mach. Intell. Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain, Yi Liu
2009	J	`jnl`	Semisupervised SVM batch mode active learning with applications to image retrieval. ACM Trans. Inf. Syst. Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu
2008	J	`jnl`	A Bayesian framework for knowledge driven regression model in micro-array data analysis. Int. J. Data Min. Bioinform. Rong Jin, Luo Si, Christina Chan
2008	A*	`conf`	Active kernel learning. ICML Steven C. H. Hoi, Rong Jin
2008	B	`conf`	Active query selection for semi-supervised clustering. ICPR Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain
2008	—	`conf`	An Extended Level Method for Efficient Multiple Kernel Learning. NIPS Zenglin Xu, Rong Jin, Irwin King, Michael R. Lyu
2008	J	`jnl`	Automated annotation of Bioinform. Shuiwang Ji, Liang Sun, Rong Jin, Sudhir Kumar, Jieping Ye
2008	—	`conf`	Multi-label Multiple Kernel Learning. NIPS Shuiwang Ji, Liang Sun, Rong Jin, Jieping Ye
2008	A*	`conf`	Rank-based distance metric learning: An application to image retrieval. CVPR Jung-Eun Lee, Rong Jin, Anil K. Jain
2008	A*	`conf`	Ranking refinement and its application to information retrieval. WWW Rong Jin, Hamed Valizadegan, Hang Li
2008	A	`conf`	Representative entry selection for profiling blogs. CIKM Jinfeng Zhuang, Steven C. H. Hoi, Aixin Sun, Rong Jin
2008	—	`conf`	Semi-Supervised Boosting for Multi-Class Classification. ECML/PKDD (2) Hamed Valizadegan, Rong Jin, Anil K. Jain
2008	A*	`conf`	Semi-Supervised Ensemble Ranking. AAAI Steven C. H. Hoi, Rong Jin
2008	—	`conf`	Semi-supervised Learning with Weakly-Related Unlabeled Data: Towards Better Text Categorization. NIPS Liu Yang, Rong Jin, Rahul Sukthankar
2008	A*	`conf`	Semi-supervised SVM batch mode active learning for image retrieval. CVPR Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu
2008	A	`conf`	Semi-supervised text categorization by active search. CIKM Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu, Irwin King
2008	A*	`conf`	Unifying discriminative visual codebook generation with classifier training for object category recognition. CVPR Liu Yang, Rong Jin, Rahul Sukthankar, Frédéric Jurie
2008	A*	`conf`	Using Knowledge Driven Matrix Factorization to Reconstruct Modular Gene Regulatory Network. AAAI Yang Zhou, Zheng Li, Xuerui Yang, Linxia Zhang, Shireesh Srivastava, Rong Jin, Christina Chan
2007	A*	`conf`	A learning framework using Green's function and kernel regularization with application to recommender system. KDD Chris H. Q. Ding, Rong Jin, Tao Li, Horst D. Simon
2007	A*	`conf`	Active Algorithm Selection. AAAI Feilong Chen, Rong Jin
2007	J	`jnl`	An empirical investigation of user term feedback in text-based targeted image search. ACM Trans. Inf. Syst. Joyce Y. Chai, Chen Zhang, Rong Jin
2007	A*	`conf`	Automated Vocabulary Acquisition and Interpretation in Multimodal Conversational Systems. ACL Yi Liu, Joyce Yue Chai, Rong Jin
2007	A	`conf`	Bayesian Active Distance Metric Learning. UAI Liu Yang, Rong Jin, Rahul Sukthankar
2007	A*	`conf`	BoostCluster: boosting clustering by pairwise constraints. KDD Yi Liu, Rong Jin, Anil K. Jain
2007	A*	`conf`	Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data. CVPR Liu Yang, Rong Jin, Caroline Pantofaru, Rahul Sukthankar
2007	—	`conf`	Efficient Convex Relaxation for Transductive Support Vector Machine. NIPS Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael R. Lyu
2007	J	`jnl`	Identifying neuronal assemblies with local and global connectivity with scale space spectral clustering. Neurocomputing Karim G. Oweiss, Rong Jin, Yasir Suhail
2007	—	`conf`	Learning distance metrics for interactive search-assisted diagnosis of mammograms. Computer-Aided Diagnosis Liu Yang, Rong Jin, Rahul Sukthankar, Bin Zheng, Lily B. Mummert, Mahadev Satyanarayanan, Mei Chen, Drazen Jukic
2007	A*	`conf`	Learning nonparametric kernel matrices from pairwise constraints. ICML Steven C. H. Hoi, Rong Jin, Michael R. Lyu
2007	A	`conf`	Localized Support Vector Machine and Its Efficient Algorithm. SDM Haibin Cheng, Pang-Ning Tan, Rong Jin
2007	—	`conf`	Michigan State University at the 2007 TREC ciQA Task. TREC Chen Zhang, Matthew Gerber, Tyler Baldwin, Steve Emelander, Joyce Yue Chai, Rong Jin
2007	J	`jnl`	Multi-Class Learning by Smoothed Boosting. Mach. Learn. Rong Jin, Jian Zhang
2007	A*	`conf`	Semi-Supervised Learning by Mixed Label Propagation. AAAI Wei Tong, Rong Jin
2007	—	`conf`	Semi-supervised Collaborative Text Classification. ECML Rong Jin, Ming Wu, Rahul Sukthankar
2007	—	`conf`	Similarity Beyond Distance Measurement. RIAO Feng Kang, Rong Jin, Steven C. H. Hoi
2007	—	`conf`	Tattoo-ID: Automatic Tattoo Image Retrieval for Suspect and Victim Identification. PCM Anil K. Jain, Jung-Eun Lee, Rong Jin
2006	—	`conf`	A Knowledge Driven Regression Model for Gene Expression and Microarray Analysis. EMBC Rong Jin, Luo Si, Shireesh Srivastava, Zheng Li, Christina Chan
2006	—	`conf`	A Mixture Model for Spike Train Ensemble Analysis Using Spectral Clustering. ICASSP (5) Rong Jin, Yasir Suhail, Karim G. Oweiss
2006	J	`jnl`	A Unified Log-Based Relevance Feedback Scheme for Image Retrieval. IEEE Trans. Knowl. Data Eng. Steven C. H. Hoi, Michael R. Lyu, Rong Jin
2006	A*	`conf`	A graph-based framework for relation propagation and its application to multi-label learning. SIGIR Ming Wu, Rong Jin
2006	J	`jnl`	A statistical framework for query translation disambiguation. ACM Trans. Asian Lang. Inf. Process. Yi Liu, Rong Jin, Joyce Y. Chai
2006	J	`jnl`	A study of mixture models for collaborative filtering. Inf. Retr. Rong Jin, Luo Si, ChengXiang Zhai
2006	A*	`conf`	An Efficient Algorithm for Local Distance Metric Learning. AAAI Liu Yang, Rong Jin, Rahul Sukthankar, Yi Liu
2006	—	`conf`	Assessing temporal and spatial evolution of clusters of functionally interdependent neurons using graph partitioning techniques. EMBC Karim G. Oweiss, Rong Jin, Feilong Chen
2006	A*	`conf`	Batch mode active learning and its application to medical image classification. ICML Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu
2006	J	`jnl`	Collaborative image retrieval via regularized metric learning. Multim. Syst. Luo Si, Rong Jin, Steven C. H. Hoi, Michael R. Lyu
2006	—	`conf`	Correlated Label Propagation with Application to Multi-label Learning. CVPR (2) Feng Kang, Rong Jin, Rahul Sukthankar
2006	—	`conf`	Generalized Maximum Margin Clustering and Unsupervised Kernel Learning. NIPS Hamed Valizadegan, Rong Jin
2006	A*	`conf`	Large-scale text categorization by batch mode active learning. WWW Steven C. H. Hoi, Rong Jin, Michael R. Lyu
2006	A*	`conf`	Semi-supervised Multi-label Learning by Constrained Non-negative Matrix Factorization. AAAI Yi Liu, Rong Jin, Liu Yang
2005	B	`conf`	A Framework for Incorporating Class Priors into Discriminative Classification. PAKDD Rong Jin, Yi Liu
2005	A*	`conf`	A Novel Approach to Model Generation for Heterogeneous Data Classification. IJCAI Rong Jin, Huan Liu
2005	—	`conf`	A Probabilistic Approach for Optimizing Spectral Clustering. NIPS Rong Jin, Chris H. Q. Ding, Feng Kang
2005	A*	`conf`	A maximum coherence model for dictionary-based cross-language information retrieval. SIGIR Yi Liu, Rong Jin, Joyce Y. Chai
2005	A*	`conf`	A smoothed boosting algorithm using probabilistic output codes. ICML Rong Jin, Jian Zhang
2005	B	`conf`	Adjusting Mixture Weights of Gaussian Mixture Model via Regularized Probabilistic Latent Semantic Analysis. PAKDD Luo Si, Rong Jin
2005	—	`conf`	Integrating User Feedback Log into Relevance Feedback by Coupled SVM for Content-Based Image Retrieval. ICDE Workshops Steven C. H. Hoi, Michael R. Lyu, Rong Jin
2005	A*	`conf`	Learn to weight terms in information retrieval using category information. ICML Rong Jin, Joyce Y. Chai, Luo Si
2005	A*	`conf`	Learning with Labeled Sessions. IJCAI Rong Jin, Huan Liu
2005	A	`conf`	Linguistic theories in efficient multimodal reference resolution: an empirical investigation. IUI Joyce Y. Chai, Zahar Prasov, Joseph Blaim, Rong Jin
2005	A*	`conf`	Query Translation Disambiguation as Graph Partitioning. AAAI Yi Liu, Rong Jin
2005	B	`conf`	Sensor Localization in an Obstructed Environment. DCOSS Chen Wang, Xiao Li, Rong Jin
2005	A*	`conf`	Study of cross lingual information retrieval using on-line translation systems. SIGIR Rong Jin, Joyce Y. Chai
2005	A	`conf`	Symmetric Statistical Translation Models for Automatic Image Annotation. SDM Feng Kang, Rong Jin
2005	A*	`conf`	User term feedback in interactive text-based image retrieval. SIGIR Chen Zhang, Joyce Y. Chai, Rong Jin
2004	A	`conf`	A Bayesian Approach toward Active Learning for Collaborative Filtering. UAI Rong Jin, Luo Si
2004	A*	`conf`	A study of methods for normalizing user ratings in collaborative filtering. SIGIR Rong Jin, Luo Si
2004	A*	`conf`	An automatic weighting scheme for collaborative filtering. SIGIR Rong Jin, Joyce Y. Chai, Luo Si
2004	A*	`conf`	Effective automatic image annotation via a coherent language model and active learning. ACM Multimedia Rong Jin, Joyce Y. Chai, Luo Si
2004	—	`conf`	MSU at ImageCLEF: Cross Language and Interactive Image Retrieval. CLEF Vineet Bansal, Chen Zhang, Joyce Y. Chai, Rong Jin
2004	A*	`conf`	Ordering patterns by combining opinions from multiple sources. KDD Pang-Ning Tan, Rong Jin
2004	A	`conf`	Regularizing translation models for better automatic image annotation. CIKM Feng Kang, Rong Jin, Joyce Y. Chai
2004	A*	`conf`	Robust feature induction for support vector machines. ICML Rong Jin, Huan Liu
2004	—	`conf`	SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data. ECML Rong Jin, Huan Liu
2004	A	`conf`	Unified filtering by combining collaborative filtering and content-based filtering via mixture model and exponential model. CIKM Luo Si, Rong Jin
2003	A*	`conf`	A Faster Iterative Scaling Algorithm for Conditional Exponential Model. ICML Rong Jin, Rong Yan, Jian Zhang, Alexander G. Hauptmann
2003	—	`conf`	A New Pairwise Ensemble Approach for Text Classification. ECML Yan Liu, Jaime G. Carbonell, Rong Jin
2003	A	`conf`	Collaborative filtering with decoupled models for preferences and ratings. CIKM Rong Jin, Luo Si, ChengXiang Zhai, James P. Callan
2003	A*	`conf`	Flexible Mixture Model for Collaborative Filtering. ICML Luo Si, Rong Jin
2003	—	`conf`	Information retrieval for OCR documents: a content-based probabilistic correction model. DRR Rong Jin, ChengXiang Zhai, Alexander G. Hauptmann
2003	—	`conf`	Informedia at TRECVID 2003 : Analyzing and Searching Broadcast News Video. TRECVID Alexander G. Hauptmann, Robert V. Baron, Ming-yu Chen, Michael G. Christel, Pinar Duygulu, C. Huang, Rong Jin, Wei-Hao Lin, Tobun D. Ng, Neema Moraveji, Norman Papernick, Cees G. M. Snoek, G. Tzanetakis, Jie Yang, Rong Yan, Howard D. Wactlar
2003	A	`conf`	Learning to identify video shots with people based on face detection. ICME Rong Jin, Alexander G. Hauptmann
2003	A*	`conf`	Modified Logistic Regression: An Approximation to SVM and Its Applications in Large-Scale Text Categorization. ICML Jian Zhang, Rong Jin, Yiming Yang, Alexander G. Hauptmann
2003	—	`conf`	Multimedia Search with Pseudo-relevance Feedback. CIVR Rong Yan, Alexander G. Hauptmann, Rong Jin
2003	A*	`conf`	Negative pseudo-relevance feedback in content-based video retrieval. ACM Multimedia Rong Yan, Alexander G. Hauptmann, Rong Jin
2003	—	`conf`	On predicting rare classes with SVM ensembles in scene classification. ICASSP (3) Rong Yan, Yan Liu, Rong Jin, Alexander G. Hauptmann
2003	A	`conf`	Preference-based Graphic Models for Collaborative Filtering. UAI Rong Jin, Luo Si, ChengXiang Zhai
2003	J	`jnl`	Statistical approaches toward automatic title generation. SIGIR Forum Rong Jin
2003	—	`conf`	Video retrieval using speech and image information. Storage and Retrieval for Media Databases Alexander G. Hauptmann, Rong Jin, Tobun Dorbin Ng
2003	—	`conf`	Web Image Retrieval Re-Ranking with Relevance Model. Web Intelligence Wei-Hao Lin, Rong Jin, Alexander G. Hauptmann
2002	B	`conf`	A New Probabilistic Model for Title Generation. COLING Rong Jin, Alexander G. Hauptmann
2002	—	`conf`	A Probabilistic Model for Camera Zoom Detection. ICPR (3) Rong Jin, Yanjun Qi, Alexander G. Hauptmann
2002	A	`conf`	A language modeling framework for resource selection and results merging. CIKM Luo Si, Rong Jin, James P. Callan, Paul Ogilvie
2002	A*	`conf`	Language model for IR using collection information. SIGIR Rong Jin, Luo Si, Alexander G. Hauptmann, James P. Callan
2002	—	`conf`	Learning with Multiple Labels. NIPS Rong Jin, Zoubin Ghahramani
2002	—	`conf`	Meta-Classification of Multimedia Classifiers. KDMCD Wei-Hao Lin, Rong Jin, Alexander G. Hauptmann
2002	—	`conf`	Multi-modal information retrieval from broadcast video using OCR and speech recognition. JCDL Alexander G. Hauptmann, Rong Jin, Tobun D. Ng
2002	A*	`conf`	Title language model for information retrieval. SIGIR Rong Jin, Alexander G. Hauptmann, ChengXiang Zhai
2002	—	`conf`	Using a probabilistic source model for comparing images. ICIP (3) Rong Jin, Alexander G. Hauptmann
2002	—	`conf`	Video Classification and Retrieval with the Informedia Digital Video Library System. TREC Alexander G. Hauptmann, Rong Yan, Yanjun Qi, Rong Jin, Michael G. Christel, Mark Derthick, Ming-yu Chen, Robert V. Baron, Wei-Hao Lin, Tobun D. Ng
2001	—	`conf`	Automatic Title Generation for Spoken Broadcast News. HLT Rong Jin, Alexander G. Hauptmann
2001	A*	`conf`	Learning to Select Good Title Words: An New Approach based on Reverse Information Retrieval. ICML Rong Jin, Alexander G. Hauptmann
2001	A*	`conf`	Meta-scoring: Automatically Evaluating Term Weighting Schemes in IR without Precision-Recall. SIGIR Rong Jin, Christos Falusos, Alexander G. Hauptmann
2001	A*	`conf`	Probabilistic Combination of Content and Links. SIGIR Susan T. Dumais, Rong Jin
2001	C	`conf`	Title Generation Using a Training Corpus. CICLing Rong Jin, Alexander G. Hauptmann
2001	A*	`conf`	Title Generation for Machine-Translated Documents. IJCAI Rong Jin, Alexander G. Hauptmann
2001	—	`conf`	Video Retrieval with the Informedia Digital Video Library System. TREC Alexander G. Hauptmann, Rong Jin, Norman Papernick, Tobun Dorbin Ng, Yanjun Qi, Ricky Houghton, Sue Thornton
2000	—	`conf`	Data Analysis for a Multimedia Library. ELSNET Summer School Alexander G. Hauptmann, Rong Jin, Howard D. Wactlar
2000	A	`conf`	Title generation for spoken broadcast news using a training corpus. INTERSPEECH Rong Jin, Alexander G. Hauptmann
1999	—	`conf`	CMU Spoken Document Retrieval in Trec-8: Analysis of the role of Term Frequency TF. TREC Matthew Siegler, Rong Jin, Alexander G. Hauptmann