Mingsheng Long

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Learning Transferable Features with Deep Adaptation Networks

▶ A deep adaptation network for learning transferable features ▶ Two important improvements: ▶ Deep adaptation of multiple task-specific layers (including output) ▶ Optimal adaptation using multiple… (More)

Transfer Feature Learning with Joint Distribution Adaptation

Mingsheng Long, Jianmin Wang, Guiguang Ding, Jia-Guang Sun, Philip S. Yu
IEEE International Conference on Computer Vision
2013

Transfer learning is established as an effective technology in computer vision for leveraging rich labeled data in the source domain to build an accurate classifier for the target domain. However,… (More)

Deep Transfer Learning with Joint Adaptation Networks

Mingsheng Long, Jianmin Wang, Michael I. Jordan
ICML
2017

Deep networks have been successfully applied to learn transferable features for adapting models from a source domain to a different target domain. In this paper, we present joint adaptation networks… (More)

Transfer Joint Matching for Unsupervised Domain Adaptation

Mingsheng Long, Jianmin Wang, Guiguang Ding, Jia-Guang Sun, Philip S. Yu
IEEE Conference on Computer Vision and Pattern…
2014

Visual domain adaptation, which learns an accurate classifier for a new domain using labeled images from an old domain, has shown promising value in computer vision yet still been a challenging… (More)

Deep Hashing Network for Efficient Similarity Retrieval

Han Zhu, Mingsheng Long, Jianmin Wang, Yue Cao
AAAI
2016

Due to the storage and retrieval efficiency, hashing has been widely deployed to approximate nearest neighbor search for large-scale multimedia retrieval. Supervised hashing, which improves the… (More)

Unsupervised Domain Adaptation with Residual Transfer Networks

Mingsheng Long, Jianmin Wang, Michael I. Jordan
NIPS
2016

The recent success of deep neural networks relies on massive amounts of labeled data. For a target task where labeled data is unavailable, domain adaptation can transfer a learner from a different… (More)

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…
2014

Domain transfer learning, which learns a target classifier using labeled data from a different distribution, has shown promising value in knowledge discovery yet still been a challenging problem.… (More)

Transfer Sparse Coding for Robust Image Representation

Mingsheng Long, Guiguang Ding, Jianmin Wang, Jia-Guang Sun, Yuchen Guo, Philip S. Yu
IEEE Conference on Computer Vision and Pattern…
2013

Sparse coding learns a set of basis functions such that each input signal can be well approximated by a linear combination of just a few of the bases. It has attracted increasing interest due to its… (More)

HashNet: Deep Learning to Hash by Continuation

Zhangjie Cao, Mingsheng Long, Jianmin Wang, Philip S. Yu
IEEE International Conference on Computer Vision…
2017

Learning to hash has been widely applied to approximate nearest neighbor search for large-scale multimedia retrieval, due to its computation efficiency and retrieval quality. Deep learning to hash,… (More)

Deep Quantization Network for Efficient Image Retrieval

Yue Cao, Mingsheng Long, Jianmin Wang, Han Zhu, Qingfu Wen
AAAI
2016

Hashing has been widely applied to approximate nearest neighbor search for large-scale multimedia retrieval. Supervised hashing improves the quality of hash coding by exploiting the semantic… (More)

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