Publications

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Preprints

  • On Catastrophic Inheritance of Large Foundation Models. Hao Chen, Bhiksha Raj, Xing Xie, Jindong Wang. [arxiv]
  • CultureLLM: Incorporating Cultural Differences into Large Language Models. Cheng Li, Mengzhou Chen, Jindong Wang, Sunayana Sitaram, Xing Xie. [arxiv]
  • SpecFormer: Guarding Vision Transformer Robustness via Maximum Singular Value Penalization. Xixu Hu, Runkai Zheng, Jindong Wang, Cheuk Hang Leung, Qi Wu, Xing Xie. [arxiv]
  • ZooPFL: Exploring Black-box Foundation Models for Personalized Federated Learning. Wang Lu, Hao Yu, Jindong Wang, Damien Teney, Haohan Wang, Yiqiang Chen, Qiang Yang, Xing Xie, Xiangyang Ji. [arxiv]
  • Meta Semantic Template for Evaluation of Large Language Models. Yachuan Liu, Liang Chen, Jindong Wang, Qiaozhu Mei, Xing Xie. [arxiv]
  • Frustratingly Easy Model Generalization by Dummy Risk Minimization. Juncheng Wang, Jindong Wang, Xixu Hu, Shujun Wang, Xing Xie. [arxiv]
  • PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts. Kaijie Zhu, Jindong Wang, Jiaheng Zhou, Zichen Wang, Hao Chen, Yidong Wang, Linyi Yang, Wei Ye, Neil Zhenqiang Gong, Yue Zhang, Xing Xie. [arxiv] [code]
  • 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]
  • Equivariant Disentangled Transformation for Domain Generalization under Combination Shift. Yivan Zhang, Jindong Wang, Xing Xie, and Masashi Sugiyama. [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

    1. Activity Recognition
      Jindong Wang , Yiqiang Chen, and Chunyu Hu
      Springer International Publishing 2023 | [ HTML ]
      1. Introduction to Transfer Learning
        Jindong Wang , and Yiqiang Chen
        Spriner Nature 2021 | [ HTML Zhihu ]

                Papers

                2024
                1. Promptbench: A unified library for evaluation of large language models
                  Kaijie Zhu, Qinlin Zhao, Hao Chen, Jindong Wang# , and Xing Xie
                  Journal of Machine Learning Research (JMLR) 2024 | [ arXiv Code ]
                2. The good, the bad, and why: Unveiling emotions in generative ai
                  Cheng Li, Jindong Wang# , Yixuan Zhang, Kaijie Zhu, Xinyi Wang, Wenxin Hou, Jianxun Lian, Fang Luo, Qiang Yang, and Xing Xie
                  International Conference on Machine Learning (ICML) 2024 | [ arXiv ]
                3. Competeai: Understanding the competition behaviors in large language model-based agents
                  Qinlin Zhao, Jindong Wang# , Yixuan Zhang, Yiqiao Jin, Kaijie Zhu, Hao Chen, and Xing Xie
                  International Conference on Machine Learning (ICML) 2024 | [ arXiv Code ]
                4. DyVal 2: Dynamic Evaluation of Large Language Models by Meta Probing Agents
                  Kaijie Zhu, Jindong Wang# , Qinlin Zhao, Ruochen Xu, and Xing Xie
                  International Conference on Machine Learning (ICML) 2024 | [ arXiv ]
                5. A General Framework for Learning from Weak Supervision
                  Hao Chen, Jindong Wang# , Lei Feng, Xiang Li, Yidong Wang, Xing Xie, Masashi Sugiyama, Rita Singh, and Bhiksha Raj
                  International Conference on Machine Learning (ICML) 2024 | [ arXiv ]
                6. Selective mixup helps with distribution shifts, but not (only) because of mixup
                  Damien Teney, Jindong Wang , and Ehsan Abbasnejad
                  International Conference on Machine Learning (ICML) 2024 | [ arXiv ]
                7. Open-Vocabulary Calibration for Vision-Language Models
                  Shuoyuan Wang, Jindong Wang , Guoqing Wang, Bob Zhang, Kaiyang Zhou, and Hongxin Wei
                  International Conference on Machine Learning (ICML) 2024 | [ arXiv ]
                8. Trustllm: Trustworthiness in large language models
                  Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, and others
                  International Conference on Machine Learning (ICML) 2024 | [ arXiv ]
                9. Position Paper: What Can Large Language Models Tell Us about Time Series Analysis
                  Ming Jin, Yifan Zhang, Wei Chen, Kexin Zhang, Yuxuan Liang, Bin Yang, Jindong Wang , Shirui Pan, and Qingsong Wen
                  International Conference on Machine Learning (ICML) 2024 | [ arXiv ]
                10. KIEval: A Knowledge-grounded Interactive Evaluation Framework for Large Language Models
                  Zhuohao Yu, Chang Gao, Wenjin Yao, Yidong Wang, Wei Ye, Jindong Wang , Xing Xie, Yue Zhang, and Shikun Zhang
                  The 62nd Annual Meeting of the Association for Computational Linguistics (ACL) 2024 | [ arXiv ]
                11. Detoxifying Large Language Models via Knowledge Editing
                  Mengru Wang, Ningyu Zhang, Ziwen Xu, Zekun Xi, Shumin Deng, Yunzhi Yao, Qishen Zhang, Linyi Yang, Jindong Wang , and Huajun Chen
                  The 62nd Annual Meeting of the Association for Computational Linguistics (ACL) 2024 | [ arXiv ]
                12. MM-Soc: Benchmarking Multimodal Large Language Models in Social Media Platforms
                  Yiqiao Jin, Minje Choi, Gaurav Verma, Jindong Wang , and Srijan Kumar
                  The 62nd Annual Meeting of the Association for Computational Linguistics (ACL) Findings 2024 | [ arXiv ]
                13. LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting
                  Haoxin Liu, Zhiyuan Zhao, Jindong Wang , Harshavardhan Kamarthi, and B Aditya Prakash
                  The 62nd Annual Meeting of the Association for Computational Linguistics (ACL) Findings 2024 | [ arXiv ]
                14. NegativePrompt: Leveraging Psychology for Large Language Models Enhancement via Negative Emotional Stimuli
                  Xu Wang, Cheng Li, Yi Chang, Jindong Wang , and Yuan Wu
                  International Joint Conference on Artificial Intelligence (IJCAI) 2024 | [ arXiv ]
                15. DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization
                  Wang Lu, Jindong Wang# , Xinwei Sun, Yiqiang Chen, Xiangyang Ji, Qiang Yang, and Xing Xie
                  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2024 | [ arXiv Code Zhihu ]
                16. DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks
                  Kaijie Zhu, Jiaao Chen, Jindong Wang# , Neil Zhenqiang Gong, Diyi Yang, and Xing Xie
                  International Conference on Learning Representation (ICLR) 2024 | [ arXiv Code ]
                  (Spotlight (Top 5%))
                17. Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks
                  Hao Chen, Jindong Wang# , Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, and Bhiksha Raj
                  International Conference on Learning Representation (ICLR) 2024 | [ arXiv Code Zhihu ]
                  (Spotlight (Top 5%))
                18. PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization
                  Yidong Wang, Zhuohao Yu, Zhengran Zeng, Linyi Yang, Cunxiang Wang, Hao Chen, Chaoya Jiang, Rui Xie, Jindong Wang , Xing Xie, and others
                  International Conference on Learning Representation (ICLR) 2024 | [ arXiv Code Zhihu ]
                19. Supervised Knowledge Makes Large Language Models Better In-context Learners
                  Linyi Yang, Shuibai Zhang, Zhuohao Yu, Guangsheng Bao, Yidong Wang, Jindong Wang , Ruochen Xu, Wei Ye, Xing Xie, Weizhu Chen, and others
                  International Conference on Learning Representation (ICLR) 2024 | [ arXiv ]
                20. A survey on evaluation of large language models
                  Yupeng Chang, Xu Wang, Jindong Wang# , Yuan Wu, Kaijie Zhu, Hao Chen, Linyi Yang, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, and others
                  ACM Transactions on Intelligent Systems and Technology (TIST) 2024 | [ Code Website Zhihu ]
                21. Generating Virtual Reality Interaction Data from Out-of-Distribution Desktop Data: An Exploration Using Stroke Gestures
                  Linping Yuan, Boyu Li, Jindong Wang , Huaming Qu, and Wei Zeng
                  The IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR) 2024 | [ ]
                22. FIXED: Frustratingly Easy Domain Generalization with Mixup
                  Wang Lu, Jindong Wang# , Han Yu, Lei Huang, Xiang Zhang, Yiqiang Chen, and Xing Xie
                  Conference on Parsimony and Learning (CPAL) 2024 | [ arXiv Code ]
                23. UP-Net: An Uncertainty-Driven Prototypical Network for Few-Shot Fault Diagnosis
                  Ge Yu, Jindong Wang , Jinhai Liu, Xi Zhang, Yiqiang Chen, and Xing Xie
                  IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2024 | [ ]
                24. Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution
                  Wang Lu, Jindong Wang# , Yidong Wang, and Xing Xie
                  SIAM Conference on Data Mining (SDM) 2024 | [ arXiv ]
                25. Optimization-Free Test-Time Adaptation for Cross-Person Activity Recognition
                  Shuoyuan Wang, Jindong Wang , Huajun Xi, Bob Zhang, Lei Zhang, and Hongxin Wei
                  Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 2024 | [ arXiv Code ]
                26. 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
                  CVPR 2024 Workshop Prompting in Vision 2024 | [ ]
                2023
                1. Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models
                  Andy Zhou, Jindong Wang , Yu-Xiong Wang, and Haohan Wang
                  Advances in Neural Information Processing Systems (NeurIPS) 2023 | [ arXiv Code ]
                2. Out-of-Distribution Generalization in Text Classification: Past, Present, and Future
                  Linyi Yang, Yaoxiao Song, Xuan Ren, Chenyang Lyu, Yidong Wang, Lingqiao Liu, Jindong Wang , Jennifer Foster, and Yue Zhang
                  The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP) 2023 | [ arXiv ]
                3. Exploring Vision-Language Models for Imbalanced Learning
                  Yidong Wang, Zhuohao Yu, Jindong Wang# , Qiang Heng, Hao Chen, Wei Ye, Rui Xie, Xing Xie, and Shikun Zhang
                  International Journal of Computer Vision (IJCV) 2023 | [ arXiv Code ]
                4. Improving Generalization of Adversarial Training via Robust Critical Fine-Tuning
                  Kaijie Zhu, Xixu Hu, Jindong Wang , Xing Xie, and Ge Yang
                  International Conference on Computer Vision (ICCV) 2023 | [ arXiv PDF Code Zhihu ]
                5. Boosting cross-domain speech recognition with self-supervision
                  Han Zhu, Gaofeng Cheng, Jindong Wang , Wenxin Hou, Pengyuan Zhang, and Yonghong Yan
                  IEEE Transactions on Audio, Speech and Language Processing (TASLP) 2023 | [ arXiv ]
                6. 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 | [ arXiv Code Video ]
                7. 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 Video Zhihu ]
                8. 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 ]
                9. 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 ]
                10. 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 ]
                11. 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 ]
                12. FedCLIP: Fast Generalization and Personalization for CLIP in Federated Learning
                  Wang Lu, Xixu Hu, Jindong Wang# , and Xing Xie
                  IEEE Data Engineering Bulletin 2023 | [ arXiv Code ]
                13. 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 ]
                  (Highlighted paper)
                14. A mutual learning framework for pruned and quantized networks
                  Xiaohai Li, Yigiang Chen, and Jindong Wang#
                  Journal of Computer Science & Technology 2023 | [ ]
                15. MetaFed: Federated Learning among Federations with Cyclic Knowledge Distillation for Personalized Healthcare
                  Yiqiang Chen, Wang Lu, Xin Qin, Jindong Wang , and Xing Xie
                  IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2023 | [ arXiv Code ]
                  (Innovation Award at IJCAI’23 FL workshop)
                2022
                1. 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 ]
                2. 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 ]
                3. 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 ]
                4. 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 ]
                5. 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 Code Website ]
                6. 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 ]
                7. 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 ]
                8. Decoupled Federated Learning for ASR with Non-IID Data
                  Han Zhu, Jindong Wang , Gaofeng Cheng, Pengyuan Zhang, and Yonghong Yan
                  Interspeech 2022 | [ arXiv PDF ]
                9. 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 ]
                10. 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 ]
                11. 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 Code ]
                12. 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 ]
                13. 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 ]
                14. 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 ]
                15. 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 ]
                16. 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 ]
                2021
                1. 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 ]
                2. Cross-domain activity recognition via substructural optimal transport
                  Wang Lu, Yiqiang Chen, Jindong Wang , and Xin Qin
                  Neurocomputing 2021 | [ arXiv HTML PDF Code Zhihu ]
                3. 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 ]
                  (500+ citations)
                4. 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 ]
                5. 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 ]
                  (Paperdigest most influencial CIKM paper)
                6. 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 ]
                7. 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 ]
                8. 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 ]
                2020
                1. 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 ]
                2. 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 ]
                  (600+ citations; most cited paper among all FL for healthcare papers)
                3. 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 ]
                4. 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 ]
                5. 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 ]
                2019
                1. 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 ]
                2. 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 ]
                3. 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 ]
                4. Cross-position activity recognition with stratified transfer learning
                  Yiqiang Chen, Jindong Wang , Meiyu Huang, and Han Yu
                  Pervasive and Mobile Computing 2019 | [ HTML PDF ]
                5. 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 ]
                6. 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 ]
                7. 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 | [ ]
                8. 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 ]
                9. 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 ]
                2018
                1. 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 ]
                2. 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 ]
                  (500+ citations; 2nd most cited paper in MM’18)
                3. 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 ]
                4. 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 ]
                2017
                1. 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 ]
                  (500+ citations; most cited paper in ICDM’17)
                2016
                1. 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 ]
                2. 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 ]
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