Jindong Wang

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	すべて	2020 年以来
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Xing Xie 谢幸Partner Research Manager, Microsoft, ACM Fellow, IEEE Fellow, CCF Fellow確認したメールアドレス: microsoft.com
Yiqiang ChenProfessor of Computer Science, Institute of Computing Technology, CAS確認したメールアドレス: ict.ac.cn
Yue ZhangWestlake University確認したメールアドレス: wias.org.cn
Bhiksha RajCarnegie Mellon University確認したメールアドレス: cs.cmu.edu
Philip S. YuProfessor of Computer Science, University of Illinons at Chicago確認したメールアドレス: cs.uic.edu
Takahiro ShinozakiTokyo Institute of Technology確認したメールアドレス: ict.e.titech.ac.jp
Han YuAssociate Professor, CCDS, Nanyang Technological University, Singapore確認したメールアドレス: ntu.edu.sg
Bernt SchieleProfessor, Max Planck Institute for Informatics, Saarland University, Saarland Informatics Campus確認したメールアドレス: mpi-inf.mpg.de
Neil Zhenqiang GongAssociate Professor, Duke University確認したメールアドレス: duke.edu
Qiang Yang (杨强）Chief AI Officer@WeBank, Prof. Emeritus @HKUST, IJCAI President 2017-19, AAAI-21 General Chair確認したメールアドレス: cse.ust.hk
Yixuan ("Janice") ZhangAssistant Professor in Computer Science, William & Mary確認したメールアドレス: wm.edu
Sinno Jialin PanThe Chinese University of Hong Kong確認したメールアドレス: cuhk.edu.hk
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of Tokyo確認したメールアドレス: k.u-tokyo.ac.jp
Qingsong Wen (文青松)Head of AI & Chief Scientist @ Squirrel AI確認したメールアドレス: gatech.edu
Damien TeneyIdiap Research Institute確認したメールアドレス: idiap.ch
Diyi YangStanford University確認したメールアドレス: stanford.edu
Haohan WangSchool of Information Sciences, University of Illinois Urbana-Champaign確認したメールアドレス: illinois.edu
Sunayana SitaramMicrosoft Research India確認したメールアドレス: microsoft.com
Srijan KumarAssistant Professor, Computer Science, Georgia Tech確認したメールアドレス: gatech.edu
Xiangliang ZhangLeonard C. Bettex Collegiate Professor, Computer Science and Engineering, University of Notre Dame確認したメールアドレス: nd.edu

フォロー

Jindong Wang

Assistant Professor, William & Mary; Ex Senior Researcher, Microsoft Research

確認したメールアドレス: wm.edu - ホームページ

machine learning transfer learning large language models generative AI


タイトル引用回数順公開年順タイトル順	引用先引用先	年
Deep learning for sensor-based activity recognition: A survey J Wang, Y Chen, S Hao, X Peng, L Hu Pattern Recognition Letters, 2019	2198	2019
A survey on evaluation of large language models Y Chang, X Wang, J Wang, Y Wu, K Zhu, H Chen, L Yang, X Yi, C Wang, ... ACM Transactions on Intelligent Systems and Technology (TIST), 2024	2090	2024
Generalizing to unseen domains: A survey on domain generalization J Wang, C Lan, C Liu, Y Ouyang, T Qin, W Lu, Y Chen, W Zeng, SY Philip IEEE transactions on knowledge and data engineering 35 (8), 8052-8072, 2022	1152	2022
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare Y Chen, X Qin, J Wang, C Yu, W Gao IEEE Intelligent Systems, 2020	982	2020
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling B Zhang, Y Wang, W Hou, H Wu, J Wang, M Okumura, T Shinozaki NeurIPS 2021, 2021	958	2021
Deep subdomain adaptation network for image classification Y Zhu, F Zhuang, J Wang, G Ke, J Chen, J Bian, H Xiong, Q He IEEE transactions on neural networks and learning systems 32 (4), 1713-1722, 2020	929	2020
Visual Domain Adaptation with Manifold Embedded Distribution Alignment J Wang, W Feng, Y Chen, H Yu, M Huang, PS Yu ACM International Conference on Multimedia (ACMMM) 2018, 2018	701	2018
Balanced distribution adaptation for transfer learning J Wang, Y Chen, S Hao, W Feng, Z Shen 2017 IEEE international conference on data mining (ICDM), 1129-1134, 2017	648	2017
Transfer Learning with Dynamic Adversarial Adaptation Network C Yu, J Wang, Y Chen, M Huang IEEE International Conference on Data Mining (ICDM) 2019, 2019	385	2019
Freematch: Self-adaptive thresholding for semi-supervised learning Y Wang, H Chen, Q Heng, W Hou, M Savvides, T Shinozaki, B Raj, Z Wu, ... ICLR, 2023	347	2023
Transfer Learning with Dynamic Distribution Adaptation J Wang, Y Chen, W Feng, H Yu, M Huang, Q Yang ACM Transactions on Intelligent Systems and Technology (ACM TIST) 11 (1), 1-25, 2020	289	2020
Stratified Transfer Learning for Cross-domain Activity Recognition J Wang, Y Chen, L Hu, X Peng, PS Yu IEEE International Conference on Pervasive Computing and Communications …, 2018	283	2018
Position: TrustLLM: Trustworthiness in large language models Y Huang, L Sun, H Wang, S Wu, Q Zhang, Y Li, C Gao, Y Huang, W Lyu, ... International Conference on Machine Learning, 20166-20270, 2024	280*	2024
AdaRNN: Adaptive Learning and Forecasting of Time Series Y Du, J Wang, W Feng, S Pan, T Qin, C Wang CIKM 2021, 2021	260	2021
Multi-representation adaptation network for cross-domain image classification Y Zhu, F Zhuang, J Wang, J Chen, Z Shi, W Wu, Q He Neural Networks 119, 214-221, 2019	247	2019
Promptbench: Towards evaluating the robustness of large language models on adversarial prompts K Zhu, J Wang, J Zhou, Z Wang, H Chen, Y Wang, L Yang, W Ye, Y Zhang, ... ACM CCS workshop LAMPS, arXiv: 2306.04528, 2024	239	2024
On the robustness of chatgpt: An adversarial and out-of-distribution perspective J Wang, X Hu, W Hou, H Chen, R Zheng, Y Wang, L Yang, H Huang, ... IEEE Data Engineering Bulletin, 2024	239	2024
Unsupervised deep anomaly detection for multi-sensor time-series signals Y Zhang, Y Chen, J Wang, Z Pan IEEE Transactions on Knowledge and Data Engineering 35 (2), 2118-2132, 2021	222	2021
SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning H Chen, R Tao, Y Fan, Y Wang, J Wang, B Schiele, X Xie, B Raj, ... ICLR, 2023	203	2023
Easy Transfer Learning By Exploiting Intra-domain Structures J Wang, Y Chen, H Yu, M Huang, Q Yang The IEEE International Conference on Multimedia and Expo (ICME) 2019, 2019	189	2019

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