Publications [DBLP] [Google Scholar] [Semantic Scholar] [Homepage]

(* Corresponding Author)

Thesis

  1. Mingsheng Long. Transfer Learning: Problems and Methods. 1-127, 2014 [PDF] (In Chinese)

Preprints

  1. On Localized Discrepancy for Domain Adaptation
    Yuchen Zhang, Mingsheng Long*, Jianmin Wang, Michael I. Jordan [arXiv 2020]

  2. Adversarial Pyramid Network for Video Domain Generalization
    Zhiyu Yao, Yunbo Wang, Xingqiang Du, Mingsheng Long*, Jianmin Wang [arXiv 2020]

Journal Articles

  1. Transferable Representation Learning with Deep Adaptation Networks
    Mingsheng Long, Yue Cao, Zhangjie Cao, Jianmin Wang, Michael I. Jordan
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 41(12):3071-3085, 2019 [Link]

  2. Deep Learning of Transferable Representation for Scalable Domain Adaptation
    Mingsheng Long, Jianmin Wang, Yue Cao, Jiaguang Sun, Philip S. Yu
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(8):2027-2040, 2016 [Link] [Code]

  3. Domain Invariant Transfer Kernel Learning
    Mingsheng Long, Jianmin Wang, Jiaguang Sun, Philip S. Yu
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(6):1519-1532, 2015 [Link] [Code]

  4. Transfer Learning with Graph Co-Regularization
    Mingsheng Long, Jianmin Wang, Guiguang Ding, Dou Shen, Qiang Yang
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 26(7):1805-1818, 2014 [Link] [Code]

  5. Adaptation Regularization: A General Framework for Transfer Learning
    Mingsheng Long, Jianmin Wang, Guiguang Ding, Sinno Jialin Pan, Philip S. Yu
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 26(5):1076-1089, 2014 [Link] [Code]

Conference Proceedings

  1. Transferable Calibration with Lower Bias and Variance in Domain Adaptation
    Ximei Wang, Mingsheng Long*, Jianmin Wang, Michael I. Jordan
    Neural Information Processing Systems (NeurIPS), 2020 (Accepted) [arXiv]

  2. Co-Tuning for Transfer Learning
    Kaichao You, Zhi Kou, Mingsheng Long*, Jianmin Wang
    Neural Information Processing Systems (NeurIPS), 2020 (Accepted)

  3. Learning to Adapt to Evolving Domains
    Hong Liu, Mingsheng Long*, Jianmin Wang, Yu Wang
    Neural Information Processing Systems (NeurIPS), 2020 (Accepted)

  4. Stochastic Normalization
    Zhi Kou, Kaichao You, Mingsheng Long*, Jianmin Wang
    Neural Information Processing Systems (NeurIPS), 2020 (Accepted)

  5. Resource Efficient Domain Adaptation
    Junguang Jiang, Ximei Wang, Mingsheng Long*, Jianmin Wang
    ACM International Conference on Multimedia (ACMMM), 2020 [PDF] [Code]

  6. Minimum Class Confusion for Versatile Domain Adaptation
    Ying Jin, Ximei Wang, Mingsheng Long*, Jianmin Wang
    European Conference on Computer Vision (ECCV), 2020 [PDF] [Code]

  7. Learning to Detect Open Classes for Universal Domain Adaptation
    Bo Fu, Zhangjie Cao, Mingsheng Long*, Jianmin Wang
    European Conference on Computer Vision (ECCV), 2020 [PDF] [Code]

  8. Negative Margin Matters: Understanding Margin in Few-shot Classification
    Bin Liu, Yue Cao, Yutong Lin, Qi Li, Zheng Zhang, Mingsheng Long, Han Hu
    European Conference on Computer Vision (ECCV), 2020 [PDF] [Code]

  9. Unsupervised Transfer Learning for Spatiotemporal Predictive Networks
    Zhiyu Yao, Yunbo Wang, Mingsheng Long*, Jianmin Wang
    International Conference on Machine Learning (ICML), 2020 [PDF] [Code]

  10. Probabilistic Video Prediction from Noisy Data with a Posterior Confidence
    Yunbo Wang, Jiajun Wu, Mingsheng Long, Joshua Tenenbaum
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 [PDF] [Code]

  11. Progressive Adversarial Networks for Fine-Grained Domain Adaptation
    Sinan Wang, Xinyang Chen, Yunbo Wang, Mingsheng Long*, Jianmin Wang
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 [PDF] [Code]

  12. Simultaneous Learning of Pivots and Representations for Cross-Domain Sentiment Classification
    Liang Li, Weirui Ye, Mingsheng Long*, Yateng Tang, Jin Xu, Jianmin Wang
    AAAI Conference on Artificial Intelligence (AAAI), 2020 [PDF]

  13. Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning
    Xinyang Chen, Sinan Wang, Bo Fu, Mingsheng Long*, Jianmin Wang
    Neural Information Processing Systems (NeurIPS), 2019 [PDF] [Code]

  14. Transferable Normalization: Towards Improving Transferability of Deep Neural Networks
    Ximei Wang, Ying Jin, Mingsheng Long*, Jianmin Wang, Michael I. Jordan
    Neural Information Processing Systems (NeurIPS), 2019 [PDF] [Code]

  15. Bridging Theory and Algorithm for Domain Adaptation
    Yuchen Zhang, Tianle Liu, Mingsheng Long*, Michael I. Jordan
    International Conference on Machine Learning (ICML), 2019 [PDF] [Appendix] [Code]

  16. Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation
    Kaichao You, Ximei Wang, Mingsheng Long*, Michael I. Jordan
    International Conference on Machine Learning (ICML), 2019 [PDF] [Code]

  17. Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers
    Hong Liu, Mingsheng Long*, Jianmin Wang, Michael I. Jordan
    International Conference on Machine Learning (ICML), 2019 [PDF] [Code]

  18. Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation
    Xinyang Chen, Sinan Wang, Mingsheng Long*, Jianmin Wang
    International Conference on Machine Learning (ICML), 2019 [PDF] [Code]

  19. Maximum-Margin Hamming Hashing
    Rong Kang, Yue Cao, Mingsheng Long*, Jianmin Wang, Philip S. Yu
    IEEE International Conference on Computer Vision (ICCV), 2019 [PDF] [Code]

  20. Universal Domain Adaptation
    Kaichao You, Mingsheng Long*, Zhangjie Cao, Jianmin Wang, Michael I. Jordan
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 [PDF] [Code]

  21. Separate to Adapt: Open Set Domain Adaptation via Progressive Separation
    Hong Liu, Zhangjie Cao, Mingsheng Long*, Jianmin Wang, Qiang Yang
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 [PDF] [Code]

  22. Learning to Transfer Examples for Partial Domain Adaptation
    Zhangjie Cao, Kaichao You, Mingsheng Long*, Jianmin Wang, Qiang Yang
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 [PDF] [Code]

  23. Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics
    Yunbo Wang, Jianjin Zhang, Hongyu Zhu, Mingsheng Long*, Jianmin Wang, Philip S. Yu
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 [PDF] [Code]

  24. Eidetic 3D LSTM: A Model for Video Prediction and Beyond
    Yunbo Wang, Lu Jiang, Ming-Hsuan Yang, Li-Jia Li, Mingsheng Long, Li Fei-Fei
    International Conference on Learning Representations (ICLR), 2019 [PDF] [Code]

  25. Transferable Curriculum for Weakly-Supervised Domain Adaptation
    Yang Shu, Zhangjie Cao, Mingsheng Long*, Jianmin Wang
    AAAI Conference on Artificial Intelligence (AAAI), 2019 [PDF] [Code]

  26. Transferable Attention for Domain Adaptation
    Ximei Wang, Liang Li, Weirui Ye, Mingsheng Long*, Jianmin Wang
    AAAI Conference on Artificial Intelligence (AAAI), 2019 [PDF]

  27. Conditional Adversarial Domain Adaptation
    Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan
    Neural Information Processing Systems (NeurIPS), 2018 [PDF] [Poster] [Code]

  28. Generalized Zero-Shot Learning with Deep Calibration Network
    Shichen Liu, Mingsheng Long*, Jianmin Wang, Michael I. Jordan
    Neural Information Processing Systems (NeurIPS), 2018 [PDF] [Code]

  29. Partial Adversarial Domain Adaptation
    Zhangjie Cao, Lijia Ma, Mingsheng Long*, Jianmin Wang
    European Conference on Computer Vision (ECCV), 2018 [PDF] [Code]

  30. Cross-Modal Hamming Hashing
    Yue Cao, Bin Liu, Mingsheng Long*, Jianmin Wang
    European Conference on Computer Vision (ECCV), 2018 [PDF]

  31. Deep Triplet Quantization
    Bin Liu, Yue Cao, Mingsheng Long*, Jianmin Wang, Jingdong Wang
    ACM International Conference on Multimedia (ACMMM), 2018 [PDF] [Code]

  32. Deep Priority Hashing
    Zhangjie Cao, Ziping Sun, Mingsheng Long*, Jianmin Wang, Philip S. Yu
    ACM International Conference on Multimedia (ACMMM), 2018 [PDF] [Code]

  33. PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning
    Yunbo Wang, Zhifeng Gao, Mingsheng Long*, Jianmin Wang, Philip S. Yu
    International Conference on Machine Learning (ICML), 2018 [PDF] [Code]

  34. PredCNN: Predictive Learning with Cascade Convolutions
    Ziru Xu, Yunbo Wang, Mingsheng Long*, Jianmin Wang
    International Joint Conference on Artificial Intelligence (IJCAI), 2018 [PDF] [Code]

  35. Partial Transfer Learning with Selective Adversarial Networks
    Zhangjie Cao, Mingsheng Long*, Jianmin Wang, Michael I. Jordan
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018 [PDF] [Slides] [Code]

  36. HashGAN: Deep Learning to Hash with Pair Conditional Wasserstein GAN
    Yue Cao, Bin Liu, Mingsheng Long*, Jianmin Wang
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018 [PDF]

  37. Deep Cauchy Hashing for Hamming Space Retrieval
    Yue Cao, Mingsheng Long*, Bin Liu, Jianmin Wang
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018 [PDF] [Code]

  38. Multi-Adversarial Domain Adaptation
    Zhongyi Pei, Zhangjie Cao, Mingsheng Long*, Jianmin Wang
    AAAI Conference on Artificial Intelligence (AAAI), 2018 [PDF] [Code]

  39. Unsupervised Domain Adaptation with Distribution Matching Machines
    Yue Cao, Mingsheng Long*, Jianmin Wang
    AAAI Conference on Artificial Intelligence (AAAI), 2018 [PDF]

  40. Transfer Adversarial Hashing for Hamming Space Retrieval
    Zhangjie Cao, Mingsheng Long*, Chao Huang, Jianmin Wang
    AAAI Conference on Artificial Intelligence (AAAI), 2018 [PDF] [Code]

  41. PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs
    Yunbo Wang, Mingsheng Long*, Jianmin Wang, Zhifeng Gao, Philip S. Yu
    Neural Information Processing Systems (NeurIPS), 2017 [PDF]

  42. Learning Multiple Tasks with Multilinear Relationship Networks
    Mingsheng Long, Zhangjie Cao, Jianmin Wang, Philip S. Yu
    Neural Information Processing Systems (NeurIPS), 2017 [PDF] [Poster] [Code]

  43. HashNet: Deep Learning to Hash by Continuation
    Zhangjie Cao, Mingsheng Long*, Jianmin Wang, Philip S. Yu
    IEEE International Conference on Computer Vision (ICCV), 2017 [PDF] [Code]

  44. Deep Transfer Learning with Joint Adaptation Networks
    Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan
    International Conference on Machine Learning (ICML), 2017 [PDF] [Slides] [Poster] [Code]

  45. Spatiotemporal Pyramid Network for Video Action Recognition
    Yunbo Wang, Mingsheng Long*, Jianmin Wang, Philip S. Yu
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 [PDF] [Slides] [Code]

  46. Deep Visual-Semantic Quantization for Efficient Image Retrieval
    Yue Cao, Mingsheng Long*, Jianmin Wang, Shichen Liu
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 [PDF] [Code]

  47. Transitive Hashing Network for Heterogeneous Multimedia Retrieval
    Zhangjie Cao, Mingsheng Long*, Jianmin Wang, Qiang Yang
    AAAI Conference on Artificial Intelligence (AAAI), 2017 [PDF]

  48. Collective Deep Quantization for Efficient Cross-Modal Retrieval
    Yue Cao, Mingsheng Long*, Jianmin Wang, Shichen Liu
    AAAI Conference on Artificial Intelligence (AAAI), 2017 [PDF] [Code]

  49. Unsupervised Domain Adaptation with Residual Transfer Networks
    Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan
    Neural Information Processing Systems (NeurIPS), 2016 [PDF] [Poster] [Code]

  50. Deep Visual-Semantic Hashing for Cross-Modal Retrieval
    Yue Cao, Mingsheng Long*, Jianmin Wang, Qiang Yang, Philip S. Yu
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016 [PDF]

  51. Composite Correlation Quantization for Efficient Multimodal Retrieval
    Mingsheng Long, Yue Cao, Jianmin Wang, Philip S. Yu
    ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2016 [PDF] [Slides] [Code]

  52. Deep Quantization Network for Efficient Image Retrieval
    Yue Cao, Mingsheng Long*, Jianmin Wang, Han Zhu, Qingfu Wen
    AAAI Conference on Artificial Intelligence (AAAI), 2016 [PDF] [Slides] [Code]

  53. Deep Hashing Network for Efficient Similarity Retrieval
    Han Zhu, Mingsheng Long*, Jianmin Wang, Yue Cao
    AAAI Conference on Artificial Intelligence (AAAI), 2016 [PDF] [Code]

  54. Learning Transferable Features with Deep Adaptation Networks
    Mingsheng Long, Yue Cao, Jianmin Wang, Michael I. Jordan
    International Conference on Machine Learning (ICML), 2015 [PDF] [Slides] [Poster] [Code] (1600+ Citations)

  55. Transfer Joint Matching for Unsupervised Domain Adaptation
    Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, Philip S. Yu
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014 [PDF] [Code]

  56. Transfer Feature Learning with Joint Distribution Adaptation
    Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, Philip S. Yu
    IEEE International Conference on Computer Vision (ICCV), 2013 [PDF] [Code]

  57. Transfer Sparse Coding for Robust Image Representation
    Mingsheng Long, Guiguang Ding, Jianmin Wang, Jiaguang Sun, Philip S. Yu
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013 [PDF] [Code]

  58. Transfer Learning with Graph Co-Regularization
    Mingsheng Long, Jianmin Wang, Guiguang Ding, Dou Shen, Qiang Yang
    AAAI Conference on Artificial Intelligence (AAAI), 2012 [PDF] [Code]

  59. Dual Transfer Learning
    Mingsheng Long, Jianmin Wang, Guiguang Ding, Wei Cheng, Xiang Zhang, Wei Wang
    SIAM International Conference on Data Mining (SDM), 2012 [PDF] (Best Paper Nominee)