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Zhangjie Cao, Kaichao You, Ziyang Zhang, Jianmin Wang, Mingsheng Long: From Big to Small: Adaptive Learning to Partial-Set Domains. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1766-1780 (2023)
Yunbo Wang, Haixu Wu, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long: PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 2208-2225 (2023)
Haixu Wu, Tengge Hu, Yong Liu, Hang Zhou, Jianmin Wang, Mingsheng Long: TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis. ICLR 2023
Xingzhuo Guo, Yuchen Zhang, Jianmin Wang, Mingsheng Long: Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms. ICML 2023: 12108-12121
Yang Shu, Xingzhuo Guo, Jialong Wu, Ximei Wang, Jianmin Wang, Mingsheng Long: CLIPood: Generalizing CLIP to Out-of-Distributions. ICML 2023: 31716-31731
Haixu Wu, Tengge Hu, Huakun Luo, Jianmin Wang, Mingsheng Long: Solving High-Dimensional PDEs with Latent Spectral Models. ICML 2023: 37417-37438
Junguang Jiang, Baixu Chen, Junwei Pan, Ximei Wang, Dapeng Liu, Jie Jiang, Mingsheng Long: ForkMerge: Overcoming Negative Transfer in Multi-Task Learning. CoRR abs/2301.12618 (2023)
Haixu Wu, Tengge Hu, Huakun Luo, Jianmin Wang, Mingsheng Long: Solving High-Dimensional PDEs with Latent Spectral Models. CoRR abs/2301.12664 (2023)
Jiaxiang Dong, Haixu Wu, Haoran Zhang, Li Zhang, Jianmin Wang, Mingsheng Long: SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling. CoRR abs/2302.00861 (2023)
Yang Shu, Xingzhuo Guo, Jialong Wu, Ximei Wang, Jianmin Wang, Mingsheng Long: CLIPood: Generalizing CLIP to Out-of-Distributions. CoRR abs/2302.00864 (2023)
Kaichao You, Anchang Bao, Guo Qin, Meng Cao, Ping Huang, Jiulong Shan, Mingsheng Long: Tune-Mode ConvBN Blocks For Efficient Transfer Learning. CoRR abs/2305.11624 (2023)
Jialong Wu, Haoyu Ma, Chaoyi Deng, Mingsheng Long: Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning. CoRR abs/2305.18499 (2023)
Yong Liu, Chenyu Li, Jianmin Wang, Mingsheng Long: Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors. CoRR abs/2305.18803 (2023)
Kaichao You, Yong Liu, Ziyang Zhang, Jianmin Wang, Michael I. Jordan, Mingsheng Long: Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs. J. Mach. Learn. Res. 23: 209:1-209:47 (2022)
Zhiyu Yao, Yunbo Wang, Jianmin Wang, Philip S. Yu, Mingsheng Long: VideoDG: Generalizing Temporal Relations in Videos to Novel Domains. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 7989-8004 (2022)
Yiwen Qiu, Jialong Wu, Zhangjie Cao, Mingsheng Long: Out-of-Dynamics Imitation Learning from Multimodal Demonstrations. CoRL 2022: 1071-1080
Geng Chen, Wendong Zhang, Han Lu, Siyu Gao, Yunbo Wang, Mingsheng Long, Xiaokang Yang: Continual Predictive Learning from Videos. CVPR 2022: 10718-10727
Junguang Jiang, Baixu Chen, Jianmin Wang, Mingsheng Long: Decoupled Adaptation for Cross-Domain Object Detection. ICLR 2022
Ximei Wang, Xinyang Chen, Jianmin Wang, Mingsheng Long: X-model: Improving Data Efficiency in Deep Learning with A Minimax Model. ICLR 2022
Jiehui Xu, Haixu Wu, Jianmin Wang, Mingsheng Long: Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy. ICLR 2022
Haixu Wu, Jialong Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long: Flowformer: Linearizing Transformers with Conservation Flows. ICML 2022: 24226-24242
Jialong Wu, Haixu Wu, Zihan Qiu, Jianmin Wang, Mingsheng Long: Supported Policy Optimization for Offline Reinforcement Learning. NeurIPS 2022
Baixu Chen, Junguang Jiang, Ximei Wang, Pengfei Wan, Jianmin Wang, Mingsheng Long: Debiased Self-Training for Semi-Supervised Learning. NeurIPS 2022
Yong Liu, Haixu Wu, Jianmin Wang, Mingsheng Long: Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting. NeurIPS 2022
Yang Shu, Zhangjie Cao, Ziyang Zhang, Jianmin Wang, Mingsheng Long: Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models. NeurIPS 2022
Junguang Jiang, Yang Shu, Jianmin Wang, Mingsheng Long: Transferability in Deep Learning: A Survey. CoRR abs/2201.05867 (2022)
Jialong Wu, Haixu Wu, Zihan Qiu, Jianmin Wang, Mingsheng Long: Supported Policy Optimization for Offline Reinforcement Learning. CoRR abs/2202.06239 (2022)
Haixu Wu, Jialong Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long: Flowformer: Linearizing Transformers with Conservation Flows. CoRR abs/2202.06258 (2022)
Baixu Chen, Junguang Jiang, Ximei Wang, Jianmin Wang, Mingsheng Long: Debiased Pseudo Labeling in Self-Training. CoRR abs/2202.07136 (2022)
Zhangjie Cao, Kaichao You, Ziyang Zhang, Jianmin Wang, Mingsheng Long: From Big to Small: Adaptive Learning to Partial-Set Domains. CoRR abs/2203.07375 (2022)
Geng Chen, Wendong Zhang, Han Lu, Siyu Gao, Yunbo Wang, Mingsheng Long, Xiaokang Yang: Continual Predictive Learning from Videos. CoRR abs/2204.05624 (2022)
Chao Huang, Zhangjie Cao, Yunbo Wang, Jianmin Wang, Mingsheng Long: MetaSets: Meta-Learning on Point Sets for Generalizable Representations. CoRR abs/2204.07311 (2022)
Yong Liu, Haixu Wu, Jianmin Wang, Mingsheng Long: Non-stationary Transformers: Rethinking the Stationarity in Time Series Forecasting. CoRR abs/2205.14415 (2022)
Yang Shu, Zhangjie Cao, Ziyang Zhang, Jianmin Wang, Mingsheng Long: Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models. CoRR abs/2206.03726 (2022)
Zhiyu Yao, Xinyang Chen, Sinan Wang, Qinyan Dai, Yumeng Li, Tanchao Zhu, Mingsheng Long: Recommender Transformers with Behavior Pathways. CoRR abs/2206.06804 (2022)
Haixu Wu, Tengge Hu, Yong Liu, Hang Zhou, Jianmin Wang, Mingsheng Long: TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis. CoRR abs/2210.02186 (2022)
Yiwen Qiu, Jialong Wu, Zhangjie Cao, Mingsheng Long: Out-of-Dynamics Imitation Learning from Multimodal Demonstrations. CoRR abs/2211.06839 (2022)
Min-Ling Zhang, Sheng-Jun Huang, Mingsheng Long: Preface. J. Comput. Sci. Technol. 36(3): 588-589 (2021)
Junguang Jiang, Yifei Ji, Ximei Wang, Yufeng Liu, Jianmin Wang, Mingsheng Long: Regressive Domain Adaptation for Unsupervised Keypoint Detection. CVPR 2021: 6780-6789
Bo Fu, Zhangjie Cao, Jianmin Wang, Mingsheng Long: Transferable Query Selection for Active Domain Adaptation. CVPR 2021: 7272-7281
Chao Huang, Zhangjie Cao, Yunbo Wang, Jianmin Wang, Mingsheng Long: MetaSets: Meta-Learning on Point Sets for Generalizable Representations. CVPR 2021: 8863-8872
Yang Shu, Zhangjie Cao, Chenyu Wang, Jianmin Wang, Mingsheng Long: Open Domain Generalization with Domain-Augmented Meta-Learning. CVPR 2021: 9624-9633
Haixu Wu, Zhiyu Yao, Jianmin Wang, Mingsheng Long: MotionRNN: A Flexible Model for Video Prediction With Spacetime-Varying Motions. CVPR 2021: 15435-15444
Xinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long: Representation Subspace Distance for Domain Adaptation Regression. ICML 2021: 1749-1759
Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long: Zoo-Tuning: Adaptive Transfer from A Zoo of Models. ICML 2021: 9626-9637
Ximei Wang, Jinghan Gao, Mingsheng Long, Jianmin Wang: Self-Tuning for Data-Efficient Deep Learning. ICML 2021: 10738-10748
Kaichao You, Yong Liu, Jianmin Wang, Mingsheng Long: LogME: Practical Assessment of Pre-trained Models for Transfer Learning. ICML 2021: 12133-12143
Haixu Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long: Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting. NeurIPS 2021: 22419-22430
Hong Liu, Jianmin Wang, Mingsheng Long: Cycle Self-Training for Domain Adaptation. NeurIPS 2021: 22968-22981
Kaichao You, Yong Liu, Mingsheng Long, Jianmin Wang: LogME: Practical Assessment of Pre-trained Models for Transfer Learning. CoRR abs/2102.11005 (2021)
Ximei Wang, Jinghan Gao, Jianmin Wang, Mingsheng Long: Self-Tuning for Data-Efficient Deep Learning. CoRR abs/2102.12903 (2021)
Haixu Wu, Zhiyu Yao, Mingsheng Long, Jianmin Wang: MotionRNN: A Flexible Model for Video Prediction with Spacetime-Varying Motions. CoRR abs/2103.02243 (2021)
Hong Liu, Jianmin Wang, Mingsheng Long: Cycle Self-Training for Domain Adaptation. CoRR abs/2103.03571 (2021)
Junguang Jiang, Yifei Ji, Ximei Wang, Yufeng Liu, Jianmin Wang, Mingsheng Long: Regressive Domain Adaptation for Unsupervised Keypoint Detection. CoRR abs/2103.06175 (2021)
Yunbo Wang, Haixu Wu, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long: PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning. CoRR abs/2103.09504 (2021)
Yang Shu, Zhangjie Cao, Chenyu Wang, Jianmin Wang, Mingsheng Long: Open Domain Generalization with Domain-Augmented Meta-Learning. CoRR abs/2104.03620 (2021)
Haixu Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long: Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting. CoRR abs/2106.13008 (2021)
Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long: Zoo-Tuning: Adaptive Transfer from a Zoo of Models. CoRR abs/2106.15434 (2021)
Junguang Jiang, Baixu Chen, Jianmin Wang, Mingsheng Long: Decoupled Adaptation for Cross-Domain Object Detection. CoRR abs/2110.02578 (2021)
Jiehui Xu, Haixu Wu, Jianmin Wang, Mingsheng Long: Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy. CoRR abs/2110.02642 (2021)
Zhiyu Yao, Yunbo Wang, Haixu Wu, Jianmin Wang, Mingsheng Long: ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning. CoRR abs/2110.03882 (2021)
Ximei Wang, Xinyang Chen, Jianmin Wang, Mingsheng Long: X-model: Improving Data Efficiency in Deep Learning with A Minimax Model. CoRR abs/2110.04572 (2021)
Yang Shu, Zhangjie Cao, Jinghan Gao, Jianmin Wang, Mingsheng Long: Omni-Training for Data-Efficient Deep Learning. CoRR abs/2110.07510 (2021)
Kaichao You, Yong Liu, Jianmin Wang, Michael I. Jordan, Mingsheng Long: Ranking and Tuning Pre-trained Models: A New Paradigm of Exploiting Model Hubs. CoRR abs/2110.10545 (2021)
Liang Li, Weirui Ye, Mingsheng Long, Yateng Tang, Jin Xu, Jianmin Wang: Simultaneous Learning of Pivots and Representations for Cross-Domain Sentiment Classification. AAAI 2020: 8220-8227
Ying Jin, Zhangjie Cao, Mingsheng Long, Jianmin Wang: Transferring Pretrained Networks to Small Data via Category Decorrelation. BMVC 2020
Sinan Wang, Xinyang Chen, Yunbo Wang, Mingsheng Long, Jianmin Wang: Progressive Adversarial Networks for Fine-Grained Domain Adaptation. CVPR 2020: 9210-9219
Yunbo Wang, Jiajun Wu, Mingsheng Long, Joshua B. Tenenbaum: Probabilistic Video Prediction From Noisy Data With a Posterior Confidence. CVPR 2020: 10827-10836
Bin Liu, Yue Cao, Yutong Lin, Qi Li, Zheng Zhang, Mingsheng Long, Han Hu: Negative Margin Matters: Understanding Margin in Few-Shot Classification. ECCV (4) 2020: 438-455
Ying Jin, Ximei Wang, Mingsheng Long, Jianmin Wang: Minimum Class Confusion for Versatile Domain Adaptation. ECCV (21) 2020: 464-480
Bo Fu, Zhangjie Cao, Mingsheng Long, Jianmin Wang: Learning to Detect Open Classes for Universal Domain Adaptation. ECCV (15) 2020: 567-583
Ying Jin, Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu, Jiaguang Sun: A Multi-Player Minimax Game for Generative Adversarial Networks. ICME 2020: 1-6
Zhiyu Yao, Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu, Jiaguang Sun: Multi-Task Learning of Generalizable Representations for Video Action Recognition. ICME 2020: 1-6
Zhiyu Yao, Yunbo Wang, Mingsheng Long, Jianmin Wang: Unsupervised Transfer Learning for Spatiotemporal Predictive Networks. ICML 2020: 10778-10788
Junguang Jiang, Ximei Wang, Mingsheng Long, Jianmin Wang: Resource Efficient Domain Adaptation. ACM Multimedia 2020: 2220-2228
Zhi Kou, Kaichao You, Mingsheng Long, Jianmin Wang: Stochastic Normalization. NeurIPS 2020
Hong Liu, Mingsheng Long, Jianmin Wang, Yu Wang: Learning to Adapt to Evolving Domains. NeurIPS 2020
Ximei Wang, Mingsheng Long, Jianmin Wang, Michael I. Jordan: Transferable Calibration with Lower Bias and Variance in Domain Adaptation. NeurIPS 2020
Kaichao You, Zhi Kou, Mingsheng Long, Jianmin Wang: Co-Tuning for Transfer Learning. NeurIPS 2020
Bin Liu, Yue Cao, Yutong Lin, Qi Li, Zheng Zhang, Mingsheng Long, Han Hu: Negative Margin Matters: Understanding Margin in Few-shot Classification. CoRR abs/2003.12060 (2020)
Ximei Wang, Mingsheng Long, Jianmin Wang, Michael I. Jordan: Transferable Calibration with Lower Bias and Variance in Domain Adaptation. CoRR abs/2007.08259 (2020)
Yuchen Zhang, Mingsheng Long, Jianmin Wang, Michael I. Jordan: On Localized Discrepancy for Domain Adaptation. CoRR abs/2008.06242 (2020)
Zhiyu Yao, Yunbo Wang, Mingsheng Long, Jianmin Wang: Unsupervised Transfer Learning for Spatiotemporal Predictive Networks. CoRR abs/2009.11763 (2020)
Jincheng Zhong, Ximei Wang, Zhi Kou, Jianmin Wang, Mingsheng Long: Bi-tuning of Pre-trained Representations. CoRR abs/2011.06182 (2020)
Mingsheng Long, Yue Cao, Zhangjie Cao, Jianmin Wang, Michael I. Jordan: Transferable Representation Learning with Deep Adaptation Networks. IEEE Trans. Pattern Anal. Mach. Intell. 41(12): 3071-3085 (2019)
Yang Shu, Zhangjie Cao, Mingsheng Long, Jianmin Wang: Transferable Curriculum for Weakly-Supervised Domain Adaptation. AAAI 2019: 4951-4958
Ximei Wang, Liang Li, Weirui Ye, Mingsheng Long, Jianmin Wang: Transferable Attention for Domain Adaptation. AAAI 2019: 5345-5352
Kaichao You, Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan: Universal Domain Adaptation. CVPR 2019: 2720-2729
Hong Liu, Zhangjie Cao, Mingsheng Long, Jianmin Wang, Qiang Yang: Separate to Adapt: Open Set Domain Adaptation via Progressive Separation. CVPR 2019: 2927-2936
Zhangjie Cao, Kaichao You, Mingsheng Long, Jianmin Wang, Qiang Yang: Learning to Transfer Examples for Partial Domain Adaptation. CVPR 2019: 2985-2994
Yunbo Wang, Jianjin Zhang, Hongyu Zhu, Mingsheng Long, Jianmin Wang, Philip S. Yu: Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics. CVPR 2019: 9154-9162
Rong Kang, Yue Cao, Mingsheng Long, Jianmin Wang, Philip S. Yu: Maximum-Margin Hamming Hashing. ICCV 2019: 8251-8260
Yunbo Wang, Lu Jiang, Ming-Hsuan Yang, Li-Jia Li, Mingsheng Long, Li Fei-Fei: Eidetic 3D LSTM: A Model for Video Prediction and Beyond. ICLR (Poster) 2019
Jianjin Zhang, Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu: Z-Order Recurrent Neural Networks for Video Prediction. ICME 2019: 230-235
Xinyang Chen, Sinan Wang, Mingsheng Long, Jianmin Wang: Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation. ICML 2019: 1081-1090
Hong Liu, Mingsheng Long, Jianmin Wang, Michael I. Jordan: Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers. ICML 2019: 4013-4022
Kaichao You, Ximei Wang, Mingsheng Long, Michael I. Jordan: Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation. ICML 2019: 7124-7133
Yuchen Zhang, Tianle Liu, Mingsheng Long, Michael I. Jordan: Bridging Theory and Algorithm for Domain Adaptation. ICML 2019: 7404-7413
Xinyang Chen, Sinan Wang, Bo Fu, Mingsheng Long, Jianmin Wang: Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning. NeurIPS 2019: 1906-1916
Ximei Wang, Ying Jin, Mingsheng Long, Jianmin Wang, Michael I. Jordan: Transferable Normalization: Towards Improving Transferability of Deep Neural Networks. NeurIPS 2019: 1951-1961
Bin Liu, Yue Cao, Mingsheng Long, Jianmin Wang, Jingdong Wang: Deep Triplet Quantization. CoRR abs/1902.00153 (2019)
Binhang Yuan, Chen Wang, Fei Jiang, Mingsheng Long, Philip S. Yu, Yuan Liu: WaveletFCNN: A Deep Time Series Classification Model for Wind Turbine Blade Icing Detection. CoRR abs/1902.05625 (2019)
Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu: Spatiotemporal Pyramid Network for Video Action Recognition. CoRR abs/1903.01038 (2019)
Zhangjie Cao, Kaichao You, Mingsheng Long, Jianmin Wang, Qiang Yang: Learning to Transfer Examples for Partial Domain Adaptation. CoRR abs/1903.12230 (2019)
Yuchen Zhang, Tianle Liu, Mingsheng Long, Michael I. Jordan: Bridging Theory and Algorithm for Domain Adaptation. CoRR abs/1904.05801 (2019)
Chen Qian, Lijie Wen, Mingsheng Long, Yanwei Li, Akhil Kumar, Jianmin Wang: Process Extraction from Texts via Multi-Task Architecture. CoRR abs/1906.02127 (2019)
Kaichao You, Mingsheng Long, Michael I. Jordan, Jianmin Wang: Learning Stages: Phenomenon, Root Cause, Mechanism Hypothesis, and Implications. CoRR abs/1908.01878 (2019)
Hong Liu, Mingsheng Long, Jianmin Wang, Michael I. Jordan: Towards Understanding the Transferability of Deep Representations. CoRR abs/1909.12031 (2019)
Ying Jin, Ximei Wang, Mingsheng Long, Jianmin Wang: Less Confusion More Transferable: Minimum Class Confusion for Versatile Domain Adaptation. CoRR abs/1912.03699 (2019)
Zhiyu Yao, Yunbo Wang, Xingqiang Du, Mingsheng Long, Jianmin Wang: Adversarial Pyramid Network for Video Domain Generalization. CoRR abs/1912.03716 (2019)
Yue Cao, Mingsheng Long, Jianmin Wang: Unsupervised Domain Adaptation With Distribution Matching Machines. AAAI 2018: 2795-2802
Zhongyi Pei, Zhangjie Cao, Mingsheng Long, Jianmin Wang: Multi-Adversarial Domain Adaptation. AAAI 2018: 3934-3941
Zhangjie Cao, Mingsheng Long, Chao Huang, Jianmin Wang: Transfer Adversarial Hashing for Hamming Space Retrieval. AAAI 2018: 6698-6705
Yue Cao, Mingsheng Long, Bin Liu, Jianmin Wang: Deep Cauchy Hashing for Hamming Space Retrieval. CVPR 2018: 1229-1237
Yue Cao, Bin Liu, Mingsheng Long, Jianmin Wang: HashGAN: Deep Learning to Hash With Pair Conditional Wasserstein GAN. CVPR 2018: 1287-1296
Zhangjie Cao, Mingsheng Long, Jianmin Wang, Michael I. Jordan: Partial Transfer Learning With Selective Adversarial Networks. CVPR 2018: 2724-2732
Zhangjie Cao, Lijia Ma, Mingsheng Long, Jianmin Wang: Partial Adversarial Domain Adaptation. ECCV (8) 2018: 139-155
Yue Cao, Bin Liu, Mingsheng Long, Jianmin Wang: Cross-Modal Hamming Hashing. ECCV (1) 2018: 207-223
Yunbo Wang, Zhifeng Gao, Mingsheng Long, Jianmin Wang, Philip S. Yu: PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning. ICML 2018: 5110-5119
Ziru Xu, Yunbo Wang, Mingsheng Long, Jianmin Wang: PredCNN: Predictive Learning with Cascade Convolutions. IJCAI 2018: 2940-2947
Bin Liu, Yue Cao, Mingsheng Long, Jianmin Wang, Jingdong Wang: Deep Triplet Quantization. ACM Multimedia 2018: 755-763
Zhangjie Cao, Ziping Sun, Mingsheng Long, Jianmin Wang, Philip S. Yu: Deep Priority Hashing. ACM Multimedia 2018: 1653-1661
Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan: Conditional Adversarial Domain Adaptation. NeurIPS 2018: 1647-1657
Shichen Liu, Mingsheng Long, Jianmin Wang, Michael I. Jordan: Generalized Zero-Shot Learning with Deep Calibration Network. NeurIPS 2018: 2009-2019
Yunbo Wang, Zhifeng Gao, Mingsheng Long, Jianmin Wang, Philip S. Yu: PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning. CoRR abs/1804.06300 (2018)
Zhangjie Cao, Lijia Ma, Mingsheng Long, Jianmin Wang: Partial Adversarial Domain Adaptation. CoRR abs/1808.04205 (2018)
Zhangjie Cao, Ziping Sun, Mingsheng Long, Jianmin Wang, Philip S. Yu: Deep Priority Hashing. CoRR abs/1809.01238 (2018)
Zhongyi Pei, Zhangjie Cao, Mingsheng Long, Jianmin Wang: Multi-Adversarial Domain Adaptation. CoRR abs/1809.02176 (2018)
Yunbo Wang, Jianjin Zhang, Hongyu Zhu, Mingsheng Long, Jianmin Wang, Philip S. Yu: Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics. CoRR abs/1811.07490 (2018)
Yunbo Wang, Zhiyu Yao, Hongyu Zhu, Mingsheng Long, Jianmin Wang, Philip S. Yu: Reversing Two-Stream Networks with Decoding Discrepancy Penalty for Robust Action Recognition. CoRR abs/1811.08362 (2018)
Zhangjie Cao, Mingsheng Long, Jianmin Wang, Qiang Yang: Transitive Hashing Network for Heterogeneous Multimedia Retrieval. AAAI 2017: 81-87
Yue Cao, Mingsheng Long, Jianmin Wang, Shichen Liu: Collective Deep Quantization for Efficient Cross-Modal Retrieval. AAAI 2017: 3974-3980
Yue Cao, Mingsheng Long, Jianmin Wang: Correlation Hashing Network for Efficient Cross-Modal Retrieval. BMVC 2017
Yue Cao, Mingsheng Long, Jianmin Wang, Shichen Liu: Deep Visual-Semantic Quantization for Efficient Image Retrieval. CVPR 2017: 916-925
Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu: Spatiotemporal Pyramid Network for Video Action Recognition. CVPR 2017: 2097-2106
Zhangjie Cao, Mingsheng Long, Jianmin Wang, Philip S. Yu: HashNet: Deep Learning to Hash by Continuation. ICCV 2017: 5609-5618
Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan: Deep Transfer Learning with Joint Adaptation Networks. ICML 2017: 2208-2217
Yunbo Wang, Mingsheng Long, Jianmin Wang, Zhifeng Gao, Philip S. Yu: PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs. NIPS 2017: 879-888
Mingsheng Long, Zhangjie Cao, Jianmin Wang, Philip S. Yu: Learning Multiple Tasks with Multilinear Relationship Networks. NIPS 2017: 1594-1603
Zhangjie Cao, Mingsheng Long, Jianmin Wang, Philip S. Yu: HashNet: Deep Learning to Hash by Continuation. CoRR abs/1702.00758 (2017)
Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan: Domain Adaptation with Randomized Multilinear Adversarial Networks. CoRR abs/1705.10667 (2017)
Zhangjie Cao, Mingsheng Long, Jianmin Wang, Michael I. Jordan: Partial Transfer Learning with Selective Adversarial Networks. CoRR abs/1707.07901 (2017)
Zhangjie Cao, Mingsheng Long, Chao Huang, Jianmin Wang: Transfer Adversarial Hashing for Hamming Space Retrieval. CoRR abs/1712.04616 (2017)
Mingsheng Long, Jianmin Wang, Yue Cao, Jia-Guang Sun, Philip S. Yu: Deep Learning of Transferable Representation for Scalable Domain Adaptation. IEEE Trans. Knowl. Data Eng. 28(8): 2027-2040 (2016)
Han Zhu, Mingsheng Long, Jianmin Wang, Yue Cao: Deep Hashing Network for Efficient Similarity Retrieval. AAAI 2016: 2415-2421
Yue Cao, Mingsheng Long, Jianmin Wang, Han Zhu, Qingfu Wen: Deep Quantization Network for Efficient Image Retrieval. AAAI 2016: 3457-3463
Yue Cao, Mingsheng Long, Jianmin Wang, Qiang Yang, Philip S. Yu: Deep Visual-Semantic Hashing for Cross-Modal Retrieval. KDD 2016: 1445-1454
Yue Cao, Mingsheng Long, Jianmin Wang, Han Zhu: Correlation Autoencoder Hashing for Supervised Cross-Modal Search. ICMR 2016: 197-204
Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan: Unsupervised Domain Adaptation with Residual Transfer Networks. NIPS 2016: 136-144
Mingsheng Long, Yue Cao, Jianmin Wang, Philip S. Yu: Composite Correlation Quantization for Efficient Multimodal Retrieval. SIGIR 2016: 579-588
Mingsheng Long, Jianmin Wang, Michael I. Jordan: Unsupervised Domain Adaptation with Residual Transfer Networks. CoRR abs/1602.04433 (2016)
Yue Cao, Mingsheng Long, Jianmin Wang: Correlation Hashing Network for Efficient Cross-Modal Retrieval. CoRR abs/1602.06697 (2016)
Mingsheng Long, Jianmin Wang, Michael I. Jordan: Deep Transfer Learning with Joint Adaptation Networks. CoRR abs/1605.06636 (2016)
Zhangjie Cao, Mingsheng Long, Qiang Yang: Transitive Hashing Network for Heterogeneous Multimedia Retrieval. CoRR abs/1608.04307 (2016)
Mingsheng Long, Jianmin Wang, Jia-Guang Sun, Philip S. Yu: Domain Invariant Transfer Kernel Learning. IEEE Trans. Knowl. Data Eng. 27(6): 1519-1532 (2015)
Mingsheng Long, Yue Cao, Jianmin Wang, Michael I. Jordan: Learning Transferable Features with Deep Adaptation Networks. ICML 2015: 97-105
Mingsheng Long, Jianmin Wang: Learning Transferable Features with Deep Adaptation Networks. CoRR abs/1502.02791 (2015)
Mingsheng Long, Jianmin Wang, Philip S. Yu: Compositional Correlation Quantization for Large-Scale Multimodal Search. CoRR abs/1504.04818 (2015)
Mingsheng Long, Jianmin Wang: Learning Multiple Tasks with Deep Relationship Networks. CoRR abs/1506.02117 (2015)
Mingsheng Long, Jianmin Wang, Guiguang Ding, Sinno Jialin Pan, Philip S. Yu: Adaptation Regularization: A General Framework for Transfer Learning. IEEE Trans. Knowl. Data Eng. 26(5): 1076-1089 (2014)
Mingsheng Long, Jianmin Wang, Guiguang Ding, Dou Shen, Qiang Yang: Transfer Learning with Graph Co-Regularization. IEEE Trans. Knowl. Data Eng. 26(7): 1805-1818 (2014)
Xiangdong Huang, Jianmin Wang, Jian Bai, Guiguang Ding, Mingsheng Long: Inherent Replica Inconsistency in Cassandra. BigData Congress 2014: 740-747
Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, Philip S. Yu: Transfer Joint Matching for Unsupervised Domain Adaptation. CVPR 2014: 1410-1417
Wu Xiang, Jianmin Wang, Mingsheng Long: Local Hybrid Coding for Image Classification. ICPR 2014: 3744-3749
Mingsheng Long, Guiguang Ding, Jianmin Wang, Jiaguang Sun, Yuchen Guo, Philip S. Yu: Transfer Sparse Coding for Robust Image Representation. CVPR 2013: 407-414
Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, Philip S. Yu: Transfer Feature Learning with Joint Distribution Adaptation. ICCV 2013: 2200-2207
Jiangfeng Shi, Mingsheng Long, Qiang Liu, Guiguang Ding, Jianmin Wang: Twin Bridge Transfer Learning for Sparse Collaborative Filtering. PAKDD (1) 2013: 496-507
Lianghao Li, Xiaoming Jin, Mingsheng Long: Topic Correlation Analysis for Cross-Domain Text Classification. AAAI 2012
Mingsheng Long, Jianmin Wang, Guiguang Ding, Dou Shen, Qiang Yang: Transfer Learning with Graph Co-Regularization. AAAI 2012
Mingsheng Long, Jianmin Wang, Guiguang Ding, Wei Cheng, Xiang Zhang, Wei Wang: Dual Transfer Learning. SDM 2012: 540-551
Mingsheng Long, Wei Cheng, Xiaoming Jin, Jianmin Wang, Dou Shen: Transfer Learning via Cluster Correspondence Inference. ICDM 2010: 917-922
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