Jindong Wang | Publications

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Preprints

Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup. Damien Teney, Jindong Wang, Ehsan Abbasnejad. [arxiv]
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations. Hao Chen, Ankit Shah, Jindong Wang, Ran Tao, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, Bhiksha Raj. [arxiv]
Exploring Vision-Language Models for Imbalanced Learning. Yidong Wang, Zhuohao Yu, Jindong Wang, Qiang Heng, Hao Chen, Wei Ye, Rui Xie, Xing Xie, Shikun Zhang. [arxiv] [code]
An Embarrassingly Simple Baseline for Imbalanced Semi-Supervised Learning. Hao Chen, Yue Fan, Yidong Wang, Jindong Wang, Bernt Schiele, Xing Xie, Marios Savvides, Bhiksha Raj. [arxiv]
FIXED: Frustratingly Easy Domain Generalization with Mixup. Wang Lu, Jindong Wang, Han Yu, Lei Huang, Xiang Zhang, Yiqiang Chen, Xing Xie. [arxiv]
Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets. Hao Chen, Ran Tao, Han Zhang, Yidong Wang, Wei Ye, Jindong Wang, Guosheng Hu, and Marios Savvides. [arxiv]
Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution. Wang Lu, Jindong Wang, Yidong Wang, Kan Ren, Yiqiang Chen, Xing Xie. [arxiv]
Equivariant Disentangled Transformation for Domain Generalization under Combination Shift. Yivan Zhang, Jindong Wang, Xing Xie, and Masashi Sugiyama. [arxiv]
Boosting Cross-Domain Speech Recognition with Self-Supervision. Han Zhu, Gaofeng Cheng, Jindong Wang, Wenxin Hou, Pengyuan Zhang, and Yonghong Yan. [arxiv]
Learning Invariant Representations across Domains and Tasks. Jindong Wang, Wenjie Feng, Chang Liu, Chaohui Yu, Mingxuan Du, Renjun Xu, Tao Qin, and Tie-Yan Liu. [arxiv]
Learning to match distributions for domain adaptation. Chaohui Yu, Jindong Wang, Chang Liu, Tao Qin, Renjun Xu, Wenjie Feng, Yiqiang Chen, and Tie-Yan Liu. [arxiv]

Books

Introduction to Transfer Learning

Jindong Wang , and Yiqiang Chen

2021 | [ HTML Zhihu ]

Papers

2023

Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning

Xin Qin, Jindong Wang^# , Shuo Ma, Wang Lu, Yongchun Zhu, Xing Xie, and Yiqiang Chen

The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2023 | [ ]
Domain-Specific Risk Minimization for Out-of-Distribution Generalization

Yi-Fan Zhang, Jindong Wang^# , Jian Liang, Zhang Zhang, Baosheng Yu, Liang Wang, Dacheng Tao, and Xing Xie

The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2023 | [ arXiv Code Zhihu ]
GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective

Linyi Yang, Shuibai Zhang, Libo Qin, Yafu Li, Yidong Wang, Hanmeng Liu, Jindong Wang , Xing Xie, and Yue Zhang

The 61st Annual Meeting of the Association for Computational Linguistics (ACL) Findings 2023 | [ arXiv Code ]
Out-of-distribution Representation Learning for Time Series Classification

Wang Lu, Jindong Wang^# , Xinwei Sun, Yiqiang Chen, and Xing Xie

International Conference on Learning Representations (ICLR) 2023 | [ arXiv Code Website Zhihu ]
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning

Yidong Wang, Hao Chen, Qiang Heng, Wenxin Hou, Yue Fan, Zhen Wu, Jindong Wang^# , Marios Savvides, Takahiro Shinozaki, Bhiksha Raj, Bernt Schiele, and Xing Xie

International Conference on Learning Representations (ICLR) 2023 | [ arXiv Code Website Zhihu ]
SoftMatch: Addressing the Quantity-Quality Tradeoff in Semi-supervised Learning

Hao Chen, Ran Tao, Yue Fan, Yidong Wang, Jindong Wang^# , Bernt Schiele, Xing Xie, Bhiksha Raj, and Marios Savvides

International Conference on Learning Representations (ICLR) 2023 | [ arXiv Code Website Zhihu ]
On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective

Jindong Wang^# , Xixu Hu, Wenxin Hou, Hao Chen, Runkai Zheng, Yidong Wang, Linyi Yang, Haojun Huang, Wei Ye, Xiubo Geng, Binxin Jiao, Yue Zhang, and Xing Xie

ICLR workshop on Trustworthy and Reliable Large-Scale Machine Learning Models (ICLR 2023 workshop) 2023 | [ arXiv Code Zhihu ]
FedCLIP: Fast Generalization and Personalization for CLIP in Federated Learning

Wang Lu, Xixu Hu, Jindong Wang^# , and Xing Xie

ICLR workshop on Trustworthy and Reliable Large-Scale Machine Learning Models (ICLR 2023 workshop) 2023 | [ arXiv Code ]
A mutual learning framework for pruned and quantized networks

Xiaohai Li, Yigiang Chen, and Jindong Wang#

Journal of Computer Science & Technology 2023 | [ ]

2022

USB: A Unified Semi-supervised Learning Benchmark

Yidong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yu-Feng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang^# , Xing Xie, and Yue Zhang

Advances in Neural Information Processing Systems (NeurIPS) 2022 | [ arXiv Blog Code Zhihu ]
Margin Calibration for Long-Tailed Visual Recognition

Yidong Wang, Bowen Zhang, Wenxin Hou, Zhen Wu, Jindong Wang^# , and Takahiro Shinozaki

Asian Conference on Machine Learning (ACML) 2022 | [ arXiv Code Zhihu ]
```
@inproceedings{wang2022margin,
  title = {Margin Calibration for Long-Tailed Visual Recognition},
  author = {Wang, Yidong and Zhang, Bowen and Hou, Wenxin and Wu, Zhen and Wang, Jindong and Shinozaki, Takahiro},
  booktitle = {Asian Conference on Machine Learning (ACML)},
  year = {2022},
  arxiv = {https://arxiv.org/abs/2112.07225},
  bibtex_show = {true},
  corr = {true},
  zhihu = {https://zhuanlan.zhihu.com/p/579153319},
  code = {https://github.com/microsoft/robustlearn}
}
```
Exploiting Unlabeled Data for Target-Oriented Opinion Words Extraction

Yidong Wang, Hao Wu, Ao Liu, Wenxin Hou, Zhen Wu, Jindong Wang , Takahiro Shinozaki, Manabu Okumura, and Yue Zhang

International Conference on Computational Linguistics (COLING) 2022 | [ arXiv PDF Code ]
Generalizing to Unseen Domains: A Survey on Domain Generalization

Jindong Wang , Cuiling Lan, Chang Liu, Yidong Ouyang, Tao Qin, Wang Lu, Yiqiang Chen, Wenjun Zeng, and Philip S. Yu

IEEE Transactions on Knowledge and Data Engineering (TKDE) 2022 | [ arXiv PDF Code Slides Website ]
```
@article{wang2022generalizing,
  title = {Generalizing to Unseen Domains: A Survey on Domain Generalization},
  author = {Wang, Jindong and Lan, Cuiling and Liu, Chang and Ouyang, Yidong and Qin, Tao and Lu, Wang and Chen, Yiqiang and Zeng, Wenjun and Yu, Philip S.},
  journal = {IEEE Transactions on Knowledge and Data Engineering (TKDE)},
  year = {2022},
  bibtex_show = {true},
  abbr = {TKDE},
  arxiv = {https://arxiv.org/abs/2103.03097},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/DeepDG},
  slides = {DGtutorial_ijcai22.pdf},
  selected = {true},
  pdf = {DG_survey_TKDE22.pdf},
  website = {https://dgresearch.github.io/}
}
```
Domain-invariant Feature Exploration for Domain Generalization

Wang Lu, Jindong Wang^# , Haoliang Li, Yiqiang Chen, and Xing Xie

Transactions on Machine Learning Research (TMLR) 2022 | [ arXiv PDF Website ]
```
@article{lu2022domain,
  title = {Domain-invariant Feature Exploration for Domain Generalization },
  author = {Lu, Wang and Wang, Jindong and Li, Haoliang and Chen, Yiqiang and Xie, Xing},
  journal = {Transactions on Machine Learning Research (TMLR)},
  year = {2022},
  bibtex_show = {true},
  corr = {true},
  abbr = {TMLR},
  website = {https://openreview.net/forum?id=0xENE7HiYm},
  arxiv = {https://arxiv.org/abs/2207.12020},
  pdf = {tmlr22-difex.pdf}
}
```
Domain generalization for activity recognition via adaptive feature fusion

Xin Qin, Jindong Wang^# , Yiqiang Chen, Wang Lu, and Xinlong Jiang

ACM Transactions on Intelligent Systems and Technology (TIST) 2022 | [ arXiv PDF ]
```
@article{qin2022domain,
  title = {Domain generalization for activity recognition via adaptive feature fusion},
  author = {Qin, Xin and Wang, Jindong and Chen, Yiqiang and Lu, Wang and Jiang, Xinlong},
  journal = {ACM Transactions on Intelligent Systems and Technology (TIST)},
  year = {2022},
  bibtex_show = {true},
  abbr = {TIST},
  corr = {true},
  arxiv = {https://arxiv.org/abs/2207.11221},
  pdf = {tist22-affar.pdf}
}
```
Memory-Guided Multi-View Multi-Domain Fake News Detection

Yongchun Zhu, Qiang Sheng, Juan Cao, Qiong Nan, Kai Shu, Minghui Wu, Jindong Wang , and Fuzhen Zhuang

IEEE Transactions on Knowledge and Data Engineering (TKDE) 2022 | [ arXiv PDF ]
```
@article{zhu2022memory,
  title = {Memory-Guided Multi-View Multi-Domain Fake News Detection},
  author = {Zhu, Yongchun and Sheng, Qiang and Cao, Juan and Nan, Qiong and Shu, Kai and Wu, Minghui and Wang, Jindong and Zhuang, Fuzhen},
  journal = {IEEE Transactions on Knowledge and Data Engineering (TKDE)},
  year = {2022},
  bibtex_show = {true},
  abbr = {TKDE},
  arxiv = {https://arxiv.org/abs/2206.12808},
  pdf = {tkde22-mdfend.pdf}
}
```
Decoupled Federated Learning for ASR with Non-IID Data

Han Zhu, Jindong Wang , Gaofeng Cheng, Pengyuan Zhang, and Yonghong Yan

Interspeech 2022 | [ arXiv PDF ]
Wav2vec-s: Semi-supervised pre-training for speech recognition

Han Zhu, Li Wang, Ying Hou, Jindong Wang , Gaofeng Cheng, Pengyuan Zhang, and Yonghong Yan

Interspeech 2022 | [ arXiv PDF ]
Personalized Federated Learning with Adaptive Batchnorm for Healthcare

Wang Lu, Jindong Wang^# , Yiqiang Chen, Xin Qin, Renjun Xu, Dimitrios Dimitriadis, and Tao Qin

IEEE Transactions on Big Data (TBD) 2022 | [ arXiv HTML PDF Code ]
```
@article{lu2022personalized,
  title = {Personalized Federated Learning with Adaptive Batchnorm for Healthcare},
  author = {Lu, Wang and Wang, Jindong and Chen, Yiqiang and Qin, Xin and Xu, Renjun and Dimitriadis, Dimitrios and Qin, Tao},
  journal = {IEEE Transactions on Big Data (TBD)},
  year = {2022},
  bibtex_show = {true},
  corr = {true},
  abbr = {TBD},
  arxiv = {https://arxiv.org/abs/2112.00734},
  pdf = {tbd22-fedap.pdf},
  html = {https://ieeexplore.ieee.org/document/9780172},
  code = {https://github.com/microsoft/PersonalizedFL}
}
```
Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition

Wang Lu, Jindong Wang^# , Yiqiang Chen, Sinno Pan, Chunyu Hu, and Xin Qin

Proceedings of the ACM on Interactive, Mobile, Wearable, and Ubiquitous Technologies (IMWUT, i.e., UbiComp) 2022 | [ arXiv PDF ]
```
@article{lu2022semantic,
  title = {Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition},
  author = {Lu, Wang and Wang, Jindong and Chen, Yiqiang and Pan, Sinno and Hu, Chunyu and Qin, Xin},
  journal = {Proceedings of the ACM on Interactive, Mobile, Wearable, and Ubiquitous Technologies (IMWUT, i.e., UbiComp)},
  year = {2022},
  abbr = {IMWUT},
  bibtex_show = {true},
  corr = {true},
  selected = {true},
  arxiv = {http://arxiv.org/abs/2206.06629},
  pdf = {imwut22-sdmix.pdf}
}
```
Adaptive Memory Networks with Self-supervised Learning for Unsupervised Anomaly Detection

Yuxin Zhang, Jindong Wang^# , Yiqiang Chen, Han Yu, and Tao Qin

IEEE Transactions on Knowledge and Data Engineering (TKDE) 2022 | [ arXiv PDF Code ]
```
@article{zhang2022adaptive,
  title = {Adaptive Memory Networks with Self-supervised Learning for Unsupervised Anomaly Detection},
  author = {Zhang, Yuxin and Wang, Jindong and Chen, Yiqiang and Yu, Han and Qin, Tao},
  journal = {IEEE Transactions on Knowledge and Data Engineering (TKDE)},
  year = {2022},
  abbr = {TKDE},
  bibtex_show = {true},
  corr = {true},
  selected = {true},
  arxiv = {https://arxiv.org/abs/2201.00464},
  pdf = {tkde22_amsl.pdf},
  code = {https://github.com/zhangyuxin621/AMSL}
}
```
Exploiting Adapters for Cross-lingual Low-resource Speech Recognition

Wenxin Hou, Han Zhu, Yidong Wang, Jindong Wang^# , Tao Qin, Renjun Xu, and Takahiro Shinozaki

IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP) 2022 | [ arXiv Code ]
```
@article{hou2022exploiting,
  title = {Exploiting Adapters for Cross-lingual Low-resource Speech Recognition},
  author = {Hou, Wenxin and Zhu, Han and Wang, Yidong and Wang, Jindong and Qin, Tao and Xu, Renjun and Shinozaki, Takahiro},
  journal = {IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)},
  year = {2022},
  abbr = {TASLP},
  bibtex_show = {true},
  arxiv = {https://arxiv.org/abs/2105.11905},
  corr = {true},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/ASR/Adapter}
}
```
Hierarchical knowledge amalgamation with dual discriminative feature alignment

Renjun Xu, Shuoying Liang, Lanyu Wen, Zhitong Guo, Xinyue Huang, Mingli Song, Jindong Wang , Xiaoxiao Xu, and Huajun Chen

Information Sciences 2022 | [ Website ]
MetaFed: Federated Learning among Federations with Cyclic Knowledge Distillation for Personalized Healthcare

Yiqiang Chen, Wang Lu, Xin Qin, Jindong Wang , and Xing Xie

IJCAI’22 federated learning workshop (FL-IJCAI) 2022 | [ arXiv Code ]

(Innovation Award)

Local and global alignments for generalizable sensor-based human activity recognition

Wang Lu, Jindong Wang^# , and Yiqiang Chen

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2022 | [ HTML ]

@inproceedings{lu2022local,
  title = {Local and global alignments for generalizable sensor-based human activity recognition},
  author = {Lu, Wang and Wang, Jindong and Chen, Yiqiang},
  booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year = {2022},
  bibtex_show = {true},
  corr = {true},
  abbr = {ICASSP},
  html = {https://ieeexplore.ieee.org/abstract/document/9747363}
}

ReMoS: Reducing Defect Inheritance in Transfer Learning via Relevant Model Slicing

Ziqi Zhang, Yuanchun Li, Jindong Wang , Bingyan Liu, Ding Li, Xiangqun Chen, Yao Guo, and Yunxin Liu

44th International Conference on Software Engineering (ICSE) 2022 | [ PDF Code Video Zhihu ]
```
@inproceedings{zhang2022remos,
  title = {ReMoS: Reducing Defect Inheritance in Transfer Learning via Relevant Model Slicing},
  author = {Zhang, Ziqi and Li, Yuanchun and Wang, Jindong and Liu, Bingyan and Li, Ding and Chen, Xiangqun and Guo, Yao and Liu, Yunxin},
  booktitle = {44th International Conference on Software Engineering (ICSE)},
  year = {2022},
  bibtex_show = {true},
  abbr = {ICSE},
  pdf = {icse22-remos.pdf},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/deep/ReMoS},
  zhihu = {https://zhuanlan.zhihu.com/p/446453487},
  video = {https://www.bilibili.com/video/BV1mi4y1C7bP},
  selected = {true}
}
```

2021

Unsupervised deep anomaly detection for multi-sensor time-series signals

Yuxin Zhang, Yiqiang Chen, Jindong Wang^# , and Zhiwen Pan

IEEE Transactions on Knowledge and Data Engineering (TKDE) 2021 | [ arXiv PDF Zhihu ]
```
@article{zhang2021unsupervised,
  title = {Unsupervised deep anomaly detection for multi-sensor time-series signals},
  author = {Zhang, Yuxin and Chen, Yiqiang and Wang, Jindong and Pan, Zhiwen},
  journal = {IEEE Transactions on Knowledge and Data Engineering (TKDE)},
  year = {2021},
  publisher = {IEEE},
  abbr = {TKDE},
  arxiv = {https://arxiv.org/abs/2107.12626},
  bibtex_show = {true},
  corr = {true},
  zhihu = {https://zhuanlan.zhihu.com/p/399411106},
  pdf = {tkde21.pdf}
}
```

Cross-domain activity recognition via substructural optimal transport

Wang Lu, Yiqiang Chen, Jindong Wang , and Xin Qin

Neurocomputing 2021 | [ arXiv HTML PDF Code Zhihu ]

@article{lu2021cross,
  title = {Cross-domain activity recognition via substructural optimal transport},
  author = {Lu, Wang and Chen, Yiqiang and Wang, Jindong and Qin, Xin},
  journal = {Neurocomputing},
  volume = {454},
  pages = {65--75},
  year = {2021},
  publisher = {Elsevier},
  abbr = {NeuCom},
  bibtex_show = {true},
  arxiv = {https://arxiv.org/abs/2102.03353},
  html = {https://www.sciencedirect.com/science/article/abs/pii/S0925231221007025},
  zhihu = {https://zhuanlan.zhihu.com/p/356904023},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/traditional/sot},
  pdf = {neurocomputing21-sot.pdf}
}

Flexmatch: Boosting semi-supervised learning with curriculum pseudo labeling

Bowen Zhang, Yidong Wang, Wenxin Hou, Hao Wu, Jindong Wang^# , Manabu Okumura, and Takahiro Shinozaki

Advances in Neural Information Processing Systems (NeurIPS) 2021 | [ arXiv PDF Code Slides Video Zhihu ]
```
@article{zhang2021flexmatch,
  title = {Flexmatch: Boosting semi-supervised learning with curriculum pseudo labeling},
  author = {Zhang, Bowen and Wang, Yidong and Hou, Wenxin and Wu, Hao and Wang, Jindong and Okumura, Manabu and Shinozaki, Takahiro},
  journal = {Advances in Neural Information Processing Systems (NeurIPS)},
  volume = {34},
  year = {2021},
  bibtex_show = {true},
  corr = {true},
  abbr = {NeurIPS},
  arxiv = {https://arxiv.org/abs/2110.08263},
  pdf = {http://jd92.wang/assets/files/flexmatch_nips21.pdf},
  code = {https://github.com/TorchSSL/TorchSSL},
  zhihu = {https://zhuanlan.zhihu.com/p/422930830},
  video = {https://www.youtube.com/watch?v=aYuUwyZl_WY},
  slides = {https://www.jianguoyun.com/p/DXeFVg8QjKnsBRibj54E},
  selected = {true}
}
```
Learning causal semantic representation for out-of-distribution prediction

Chang Liu, Xinwei Sun, Jindong Wang , Haoyue Tang, Tao Li, Tao Qin, Wei Chen, and Tie-Yan Liu

Thirty-Fifth Conference on Neural Information Processing Systems (NeurIPS) 2021 | [ arXiv PDF Code ]
```
@inproceedings{liu2021learning,
  title = {Learning causal semantic representation for out-of-distribution prediction},
  author = {Liu, Chang and Sun, Xinwei and Wang, Jindong and Tang, Haoyue and Li, Tao and Qin, Tao and Chen, Wei and Liu, Tie-Yan},
  booktitle = {Thirty-Fifth Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  bibtex_show = {true},
  abbr = {NeurIPS},
  arxiv = {https://arxiv.org/abs/2011.01681},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/deep/CSG},
  pdf = {nips21-csusalcsg.pdf}
}
```
Adarnn: Adaptive learning and forecasting of time series

Yuntao Du, Jindong Wang^# , Wenjie Feng, Sinno Pan, Tao Qin, Renjun Xu, and Chongjun Wang

The 30th ACM International Conference on Information & Knowledge Management (CIKM) 2021 | [ arXiv PDF Code ]
```
@inproceedings{du2021adarnn,
  title = {Adarnn: Adaptive learning and forecasting of time series},
  author = {Du, Yuntao and Wang, Jindong and Feng, Wenjie and Pan, Sinno and Qin, Tao and Xu, Renjun and Wang, Chongjun},
  booktitle = {The 30th ACM International Conference on Information \& Knowledge Management (CIKM)},
  pages = {402--411},
  year = {2021},
  bibtex_show = {true},
  abbr = {CIKM},
  corr = {true},
  selected = {true},
  arxiv = {https://arxiv.org/abs/2108.04443},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/deep/adarnn},
  pdf = {cikm21-adarnn.pdf}
}
```
Cross-domain Speech Recognition with Unsupervised Character-level Distribution Matching

Wenxin Hou, Jindong Wang^# , Xu Tan, Tao Qin, and Takahiro Shinozaki

Interspeech 2021 | [ arXiv PDF Code ]
```
@inproceedings{hou2021cross,
  title = {Cross-domain Speech Recognition with Unsupervised Character-level Distribution Matching},
  author = {Hou, Wenxin and Wang, Jindong and Tan, Xu and Qin, Tao and Shinozaki, Takahiro},
  booktitle = {Interspeech},
  year = {2021},
  bibtex_show = {true},
  abbr = {IS},
  corr = {true},
  pdf = {a25_interspeech21.pdf},
  arxiv = {https://arxiv.org/abs/2104.07491},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/ASR/CMatch}
}
```
Generalizing to Unseen Domains: A Survey on Domain Generalization

Jindong Wang , Cuiling Lan, Chang Liu, Yidong Ouyang, Wenjun Zeng, and Tao Qin

International Joint Conference on Artificial Intelligence (IJCAI) 2021 | [ arXiv PDF Code Slides ]
```
@inproceedings{wang2021generalizing,
  title = {Generalizing to Unseen Domains: A Survey on Domain Generalization},
  author = {Wang, Jindong and Lan, Cuiling and Liu, Chang and Ouyang, Yidong and Zeng, Wenjun and Qin, Tao},
  booktitle = {International Joint Conference on Artificial Intelligence (IJCAI)},
  year = {2021},
  bibtex_show = {true},
  abbr = {IJCAI},
  arxiv = {https://arxiv.org/abs/2103.03097},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/DeepDG},
  slides = {DGSurvey-ppt.pdf},
  pdf = {DG_survey_TKDE22.pdf}
}
```
MixSpeech: Data Augmentation for Low-resource Automatic Speech Recognition

Linghui Meng, Jin Xu, Xu Tan, Jindong Wang , Tao Qin, and Bo Xu

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2021 | [ arXiv ]
```
@inproceedings{meng2021mixspeech,
  title = {MixSpeech: Data Augmentation for Low-resource Automatic Speech Recognition},
  author = {Meng, Linghui and Xu, Jin and Tan, Xu and Wang, Jindong and Qin, Tao and Xu, Bo},
  booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages = {7008--7012},
  year = {2021},
  organization = {IEEE},
  abbr = {ICASSP},
  bibtex_show = {true},
  arxiv = {https://arxiv.org/pdf/2102.12664}
}
```

2020

Deep subdomain adaptation network for image classification

Yongchun Zhu, Fuzhen Zhuang, Jindong Wang , Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, and Qing He

IEEE transactions on neural networks and learning systems 2020 | [ HTML PDF Code ]
```
@article{zhu2020deep,
  title = {Deep subdomain adaptation network for image classification},
  author = {Zhu, Yongchun and Zhuang, Fuzhen and Wang, Jindong and Ke, Guolin and Chen, Jingwu and Bian, Jiang and Xiong, Hui and He, Qing},
  journal = {IEEE transactions on neural networks and learning systems},
  volume = {32},
  number = {4},
  pages = {1713--1722},
  year = {2020},
  publisher = {IEEE},
  bibtex_show = {true},
  pdf = {a24tnnls20.pdf},
  html = {https://ieeexplore.ieee.org/document/9085896},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/DeepDA},
  abbr = {TNNLS}
}
```
Fedhealth: A federated transfer learning framework for wearable healthcare

Yiqiang Chen, Xin Qin, Jindong Wang , Chaohui Yu, and Wen Gao

IEEE Intelligent Systems 2020 | [ HTML PDF ]
```
@article{chen2020fedhealth,
  title = {Fedhealth: A federated transfer learning framework for wearable healthcare},
  author = {Chen, Yiqiang and Qin, Xin and Wang, Jindong and Yu, Chaohui and Gao, Wen},
  journal = {IEEE Intelligent Systems},
  volume = {35},
  number = {4},
  pages = {83--93},
  year = {2020},
  publisher = {IEEE},
  pdf = {a21_intesys20.pdf},
  html = {https://ieeexplore.ieee.org/document/9076082},
  bibtex_show = {true}
}
```
Transfer learning with dynamic distribution adaptation

Jindong Wang , Yiqiang Chen, Wenjie Feng, Han Yu, Meiyu Huang, and Qiang Yang

ACM Transactions on Intelligent Systems and Technology (TIST) 2020 | [ HTML PDF Code ]
```
@article{wang2020transfer,
  title = {Transfer learning with dynamic distribution adaptation},
  author = {Wang, Jindong and Chen, Yiqiang and Feng, Wenjie and Yu, Han and Huang, Meiyu and Yang, Qiang},
  journal = {ACM Transactions on Intelligent Systems and Technology (TIST)},
  volume = {11},
  number = {1},
  pages = {1--25},
  year = {2020},
  publisher = {ACM New York, NY, USA},
  pdf = {a17_tist19.pdf},
  html = {https://dl.acm.org/doi/abs/10.1145/3360309},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/deep/DeepMEDA},
  bibtex_show = {true},
  abbr = {TIST}
}
```
Joint Partial Optimal Transport for Open Set Domain Adaptation.

Renjun Xu, Pelen Liu, Yin Zhang, Fang Cai, Jindong Wang , Shuoying Liang, Heting Ying, and Jianwei Yin

International Joint Conference on Artificial Intelligence (IJCAI) 2020 | [ HTML PDF ]
```
@inproceedings{xu2020joint,
  title = {Joint Partial Optimal Transport for Open Set Domain Adaptation.},
  author = {Xu, Renjun and Liu, Pelen and Zhang, Yin and Cai, Fang and Wang, Jindong and Liang, Shuoying and Ying, Heting and Yin, Jianwei},
  booktitle = {International Joint Conference on Artificial Intelligence (IJCAI)},
  pages = {2540--2546},
  year = {2020},
  bibtex_show = {true},
  abbr = {IJCAI},
  html = {https://www.ijcai.org/Proceedings/2020/352},
  pdf = {a23_ijcai20.pdf}
}
```
Reliable weighted optimal transport for unsupervised domain adaptation

Renjun Xu, Pelen Liu, Liyan Wang, Chao Chen, and Jindong Wang#

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020 | [ HTML PDF ]
```
@inproceedings{xu2020reliable,
  title = {Reliable weighted optimal transport for unsupervised domain adaptation},
  author = {Xu, Renjun and Liu, Pelen and Wang, Liyan and Chen, Chao and Wang, Jindong},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  pages = {4394--4403},
  year = {2020},
  abbr = {CVPR},
  bibtex_show = {true},
  html = {http://openaccess.thecvf.com/content_CVPR_2020/html/Xu_Reliable_Weighted_Optimal_Transport_for_Unsupervised_Domain_Adaptation_CVPR_2020_paper.html},
  pdf = {a22_cvpr20.pdf}
}
```

2019

Cross-dataset activity recognition via adaptive spatial-temporal transfer learning

Xin Qin, Yiqiang Chen, Jindong Wang , and Chaohui Yu

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 2019 | [ HTML PDF ]
```
@article{qin2019cross,
  title = {Cross-dataset activity recognition via adaptive spatial-temporal transfer learning},
  author = {Qin, Xin and Chen, Yiqiang and Wang, Jindong and Yu, Chaohui},
  journal = {Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT)},
  volume = {3},
  number = {4},
  pages = {1--25},
  year = {2019},
  publisher = {ACM New York, NY, USA},
  pdf = {a20_ubicomp20.pdf},
  html = {https://dl.acm.org/doi/abs/10.1145/3369818},
  bibtex_show = {true},
  abbr = {IMWUT}
}
```

Transfer channel pruning for compressing deep domain adaptation models

Chaohui Yu, Jindong Wang , Yiqiang Chen, and Xin Qin

International Journal of Machine Learning and Cybernetics (JMLC) 2019 | [ HTML PDF Code ]

@article{yu2019transfer,
  title = {Transfer channel pruning for compressing deep domain adaptation models},
  author = {Yu, Chaohui and Wang, Jindong and Chen, Yiqiang and Qin, Xin},
  journal = {International Journal of Machine Learning and Cybernetics (JMLC)},
  volume = {10},
  number = {11},
  pages = {3129--3144},
  year = {2019},
  publisher = {Springer},
  html = {http://link.springer.com/article/10.1007/s13042-019-01004-6},
  pdf = {a18_ijmlc19.pdf},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/deep/TCP},
  bibtex_show = {true},
  abbr = {JMLC}
}

Multi-representation adaptation network for cross-domain image classification

Yongchun Zhu, Fuzhen Zhuang, Jindong Wang , Jingwu Chen, Zhiping Shi, Wenjuan Wu, and Qing He

Neural Networks 2019 | [ HTML PDF Code ]
```
@article{zhu2019multi,
  title = {Multi-representation adaptation network for cross-domain image classification},
  author = {Zhu, Yongchun and Zhuang, Fuzhen and Wang, Jindong and Chen, Jingwu and Shi, Zhiping and Wu, Wenjuan and He, Qing},
  journal = {Neural Networks},
  volume = {119},
  pages = {214--221},
  year = {2019},
  publisher = {Elsevier},
  html = {https://doi.org/10.1016/j.neunet.2019.07.010},
  pdf = {a19_neunet19.pdf},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/deep/MRAN},
  bibtex_show = {true},
  abbr = {NeuNet}
}
```
Cross-position activity recognition with stratified transfer learning

Yiqiang Chen, Jindong Wang , Meiyu Huang, and Han Yu

Pervasive and Mobile Computing 2019 | [ HTML PDF ]
```
@article{chen2019cross,
  title = {Cross-position activity recognition with stratified transfer learning},
  author = {Chen, Yiqiang and Wang, Jindong and Huang, Meiyu and Yu, Han},
  journal = {Pervasive and Mobile Computing},
  volume = {57},
  pages = {1--13},
  year = {2019},
  publisher = {Elsevier},
  html = {https://doi.org/10.1016/j.pmcj.2019.04.004},
  pdf = {a14_pmc19.pdf},
  bibtex_show = {true},
  abbr = {PMC}
}
```
Deep learning for sensor-based activity recognition: A survey

Jindong Wang , Yiqiang Chen, Shuji Hao, Xiaohui Peng, and Lisha Hu

Pattern Recognition Letters 2019 | [ HTML PDF ]
```
@article{wang2019deep,
  title = {Deep learning for sensor-based activity recognition: A survey},
  author = {Wang, Jindong and Chen, Yiqiang and Hao, Shuji and Peng, Xiaohui and Hu, Lisha},
  journal = {Pattern Recognition Letters},
  volume = {119},
  pages = {3--11},
  year = {2019},
  publisher = {Elsevier},
  html = {https://www.sciencedirect.com/science/article/pii/S016786551830045X},
  pdf = {a10_prl18.pdf},
  bibtex_show = {true},
  abbr = {PRL}
}
```
Transfer learning with dynamic adversarial adaptation network

Chaohui Yu, Jindong Wang , Yiqiang Chen, and Meiyu Huang

2019 IEEE International Conference on Data Mining (ICDM) 2019 | [ PDF Code ]
```
@inproceedings{yu2019transfes,
  title = {Transfer learning with dynamic adversarial adaptation network},
  author = {Yu, Chaohui and Wang, Jindong and Chen, Yiqiang and Huang, Meiyu},
  booktitle = {2019 IEEE International Conference on Data Mining (ICDM)},
  pages = {778--786},
  year = {2019},
  organization = {IEEE},
  bibtex_show = {true},
  abbr = {ICDM},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/deep/DAAN},
  pdf = {a16_icdm19.pdf}
}
```
DrowsyDet: A Mobile Application for Real-time Driver Drowsiness Detection

Chaohui Yu, Xin Qin, Yiqiang Chen, Jindong Wang , and Chenchen Fan

Ubiquitous Intelligence Computing 2019 | [ ]
```
@inproceedings{yu2019drowsydet,
  title = {DrowsyDet: A Mobile Application for Real-time Driver Drowsiness Detection},
  author = {Yu, Chaohui and Qin, Xin and Chen, Yiqiang and Wang, Jindong and Fan, Chenchen},
  booktitle = {Ubiquitous Intelligence Computing},
  pages = {425--432},
  year = {2019},
  organization = {IEEE},
  bibtex_show = {true},
  abbr = {UIC}
}
```
Easy transfer learning by exploiting intra-domain structures

Jindong Wang , Yiqiang Chen, Han Yu, Meiyu Huang, and Qiang Yang

2019 IEEE International Conference on Multimedia and Expo (ICME) 2019 | [ PDF Code ]
```
@inproceedings{wang2019easy,
  title = {Easy transfer learning by exploiting intra-domain structures},
  author = {Wang, Jindong and Chen, Yiqiang and Yu, Han and Huang, Meiyu and Yang, Qiang},
  booktitle = {2019 IEEE International Conference on Multimedia and Expo (ICME)},
  pages = {1210--1215},
  year = {2019},
  organization = {IEEE},
  bibtex_show = {true},
  abbr = {ICME},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/traditional/EasyTL},
  pdf = {a13_icme19.pdf}
}
```

Accelerating deep unsupervised domain adaptation with transfer channel pruning

Chaohui Yu, Jindong Wang , Yiqiang Chen, and Zijing Wu

2019 International Joint Conference on Neural Networks (IJCNN) 2019 | [ arXiv PDF Code ]

@inproceedings{yu2019accelerating,
  title = {Accelerating deep unsupervised domain adaptation with transfer channel pruning},
  author = {Yu, Chaohui and Wang, Jindong and Chen, Yiqiang and Wu, Zijing},
  booktitle = {2019 International Joint Conference on Neural Networks (IJCNN)},
  pages = {1--8},
  year = {2019},
  organization = {IEEE},
  bibtex_show = {true},
  abbr = {IJCNN},
  arxiv = {https://arxiv.org/pdf/1904.02654.pdf},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/deep/TCP},
  pdf = {ijcnn19-tcp.pdf}
}

2018

OKRELM: online kernelized and regularized extreme learning machine for wearable-based activity recognition

Lisha Hu, Yiqiang Chen, Jindong Wang , Chunyu Hu, and Xinlong Jiang

International Journal of Machine Learning and Cybernetics (JMLC) 2018 | [ HTML PDF ]
```
@article{hu2018okrelm,
  title = {OKRELM: online kernelized and regularized extreme learning machine for wearable-based activity recognition},
  author = {Hu, Lisha and Chen, Yiqiang and Wang, Jindong and Hu, Chunyu and Jiang, Xinlong},
  journal = {International Journal of Machine Learning and Cybernetics (JMLC)},
  volume = {9},
  number = {9},
  pages = {1577--1590},
  year = {2018},
  publisher = {Springer},
  html = {https://link.springer.com/article/10.1007/s13042-017-0666-8?wt_mc=Internal.Event.1.SEM.ArticleAuthorOnlineFirst#enumeration},
  pdf = {a06_ijmlc.pdf},
  bibtex_show = {true},
  abbr = {JMLC}
}
```
Visual domain adaptation with manifold embedded distribution alignment

Jindong Wang , Wenjie Feng, Yiqiang Chen, Han Yu, Meiyu Huang, and Philip S Yu

The 26th ACM international conference on Multimedia 2018 | [ PDF Supp Code Poster ]

(400+ citations; 2nd most cited paper in MM’18)
```
@inproceedings{wang2018visual,
  title = {Visual domain adaptation with manifold embedded distribution alignment},
  author = {Wang, Jindong and Feng, Wenjie and Chen, Yiqiang and Yu, Han and Huang, Meiyu and Yu, Philip S},
  booktitle = {The 26th ACM international conference on Multimedia},
  pages = {402--410},
  year = {2018},
  bibtex_show = {true},
  abbr = {ACMMM},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/traditional/MEDA},
  pdf = {a11_mm18.pdf},
  supp = {https://www.jianguoyun.com/p/DRuWOFkQjKnsBRjkr2E},
  poster = {poster_mm18.pdf},
  selected = {true},
  special = {400+ citations; 2nd most cited paper in MM'18}
}
```
Deep transfer learning for cross-domain activity recognition

Jindong Wang , Vincent W Zheng, Yiqiang Chen, and Meiyu Huang

proceedings of the 3rd International Conference on Crowd Science and Engineering 2018 | [ HTML PDF ]
```
@inproceedings{wang2018deep,
  title = {Deep transfer learning for cross-domain activity recognition},
  author = {Wang, Jindong and Zheng, Vincent W and Chen, Yiqiang and Huang, Meiyu},
  booktitle = {proceedings of the 3rd International Conference on Crowd Science and Engineering},
  pages = {1--8},
  year = {2018},
  bibtex_show = {true},
  abbr = {ICCSE},
  pdf = {a12_iccse18.pdf},
  html = {https://dl.acm.org/citation.cfm?id=3265705}
}
```
Stratified transfer learning for cross-domain activity recognition

Jindong Wang , Yiqiang Chen, Lisha Hu, Xiaohui Peng, and S Yu Philip

IEEE international conference on pervasive computing and communications (PerCom) 2018 | [ PDF Code ]
```
@inproceedings{wang2018stratified,
  title = {Stratified transfer learning for cross-domain activity recognition},
  author = {Wang, Jindong and Chen, Yiqiang and Hu, Lisha and Peng, Xiaohui and Philip, S Yu},
  booktitle = {IEEE international conference on pervasive computing and communications (PerCom)},
  pages = {1--10},
  year = {2018},
  organization = {IEEE},
  bibtex_show = {true},
  abbr = {PerCom},
  code = {https://github.com/jindongwang/activityrecognition/tree/master/code/percom18_stl},
  pdf = {a09_percom18.pdf}
}
```

2017

Balanced distribution adaptation for transfer learning

Jindong Wang , Yiqiang Chen, Shuji Hao, Wenjie Feng, and Zhiqi Shen

IEEE international conference on data mining (ICDM) 2017 | [ HTML PDF Code ]

(400+ citations; most cited paper in ICDM’17)
```
@inproceedings{wang2017balanced,
  title = {Balanced distribution adaptation for transfer learning},
  author = {Wang, Jindong and Chen, Yiqiang and Hao, Shuji and Feng, Wenjie and Shen, Zhiqi},
  booktitle = {IEEE international conference on data mining (ICDM)},
  pages = {1129--1134},
  year = {2017},
  organization = {IEEE},
  bibtex_show = {true},
  abbr = {ICDM},
  code = {https://github.com/jindongwang/transferlearning/tree/master/code/BDA},
  pdf = {a08_icdm17.pdf},
  html = {http://ieeexplore.ieee.org/document/8215613/?part=1},
  selected = {true},
  special = {400+ citations; most cited paper in ICDM'17}
}
```

2016

Ocean: A new opportunistic computing model for wearable activity recognition

Yiqiang Chen, Yang Gu, Xinlong Jiang, and Jindong Wang#

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct 2016 | [ HTML PDF ]
```
@inproceedings{chen2016ocean,
  title = {Ocean: A new opportunistic computing model for wearable activity recognition},
  author = {Chen, Yiqiang and Gu, Yang and Jiang, Xinlong and Wang, Jindong},
  booktitle = {Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct},
  pages = {33--36},
  year = {2016},
  bibtex_show = {true},
  abbr = {UbiComp},
  pdf = {a04_ubicomp16.pdf},
  html = {http://dl.acm.org/citation.cfm?id=2971453}
}
```
Less annotation on personalized activity recognition using context data

Lisha Hu, Yiqiang Chen, Shuangquan Wang, Jindong Wang , Jianfei Shen, Xinlong Jiang, and Zhiqi Shen

2016 Intl IEEE Conferences on Ubiquitous Intelligence Computing (UIC) 2016 | [ HTML PDF ]
```
@inproceedings{hu2016less,
  title = {Less annotation on personalized activity recognition using context data},
  author = {Hu, Lisha and Chen, Yiqiang and Wang, Shuangquan and Wang, Jindong and Shen, Jianfei and Jiang, Xinlong and Shen, Zhiqi},
  booktitle = {2016 Intl IEEE Conferences on Ubiquitous Intelligence Computing (UIC)},
  pages = {327--332},
  year = {2016},
  organization = {IEEE},
  bibtex_show = {true},
  abbr = {UIC},
  pdf = {a02_uic16.pdf},
  html = {http://ieeexplore.ieee.org/abstract/document/7816862/}
}
```