Mingsheng Long


Mingsheng Long

Biography


I am an assistant professor and Ph.D supervisor in the School of Software, Tsinghua University. My research interests include machine learning and big data, with specific focus on deep learning, transfer learning, and scalable machine learning methods, systems, and applications.

I am leading the Machine Learning Group in the National Engineering Laboratory for Big Data Systems. I am looking for highly motivated graduate or undergraduate students to work on machine learning and big data analysis. Please send me your CV if you are interested.

My Quote

Everything should be made as simple as possible, but no simpler.” --Albert Einstein

Research Interests


Education


Research Experience


Publications [DBLP] [Google Scholar]


PhD Thesis

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

Journal Articles

  1. 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]

  2. 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]

  3. 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]

  4. 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. Multi-Adversarial Domain Adaptation
    Zhongyi Pei, Mingsheng Long*, Zhangjie Cao, Jianmin Wang
    AAAI Conference on Artificial Intelligence (AAAI), 2018 (Accepted)

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

  3. Transfer Adversarial Hashing for Hamming Space Retrieval
    Zhangjie Cao, Mingsheng Long*, Chao Huang, Jianmin Wang
    AAAI Conference on Artificial Intelligence (AAAI), 2018 (Accepted)

  4. 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 (NIPS), 2017 (Accepted)

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

  6. 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@Github]

  7. Correlation Hashing Network for Efficient Cross-Modal Retrieval
    Yue Cao, Mingsheng Long*, Jianmin Wang, Philip S. Yu
    British Machine Vision Conference (BMVC), 2017 [PDF]

  8. 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@Github]

  9. 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@Github]

  10. 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@Github]

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

  12. 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@Github]

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

  14. 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]

  15. 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]

  16. Correlation Autoencoder Hashing for Supervised Cross-Modal Search
    Yue Cao, Mingsheng Long*, Jianmin Wang, Han Zhu
    ACM International Conference on Multimedia Retrieval (ICMR), 2016

  17. 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]

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

  19. 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@Github]

  20. Local Hybrid Coding for Image Classification
    Wu Xiang, Jianmin Wang, Mingsheng Long
    International Conference on Pattern Recognition (ICPR), 2014

  21. Inherent Replica Inconsistency in Cassandra
    Xiangdong Huang, Jianmin Wang, Jian Bai, Guiguang Ding, Mingsheng Long
    International Congress on Big Data (BigData), 2014

  22. 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]

  23. 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]

  24. 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]

  25. Twin Bridge Transfer Learning for Sparse Collaborative Filtering
    Jiangfeng Shi, Mingsheng Long, Qiang Liu, Guiguang Ding, Jianmin Wang
    Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2013

  26. 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]

  27. Topic Correlation Analysis for Cross-Domain Text Classification
    Lianghao Li, Xiaoming Jin, Mingsheng Long
    AAAI Conference on Artificial Intelligence (AAAI), 2012 [PDF] [Code]

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

  29. Transfer Learning via Cluster Correspondence Inference
    Mingsheng Long, Wei Cheng, Xiaoming Jin, Jianmin Wang, Dou Shen
    IEEE International Conference on Data Mining (ICDM), 2010 (Short Paper)

Preprints & Technical Reports

  1. Domain Adaptation with Randomized Multilinear Adversarial Networks
    Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan, 2017 [arXiv]

  2. Partial Transfer Learning with Selective Adversarial Networks
    Zhangjie Cao, Mingsheng Long*, Jianmin Wang, Michael I. Jordan, 2017 [arXiv]

Honors and Awards


Professional Activities


Organizer | Chair

PC Member | Reviewer

Research Grants


Teaching


Students


Graduates

Undergraduates