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Han Yu

GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learning


Sep 05, 2021
Zelei Liu, Yuanyuan Chen, Han Yu, Yang Liu, Lizhen Cui

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Towards Out-Of-Distribution Generalization: A Survey


Aug 31, 2021
Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, Peng Cui

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Personalised Federated Learning: A Combinational Approach


Aug 22, 2021
Sone Kyaw Pye, Han Yu

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* in Proceedings of the 1st International Student Conference on Artificial Intelligence (STCAI'21), 2021 
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Noise-Resistant Deep Metric Learning with Probabilistic Instance Filtering


Aug 03, 2021
Chang Liu, Han Yu, Boyang Li, Zhiqi Shen, Zhanning Gao, Peiran Ren, Xuansong Xie, Lizhen Cui, Chunyan Miao

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* Submitted to TPAMI. arXiv admin note: substantial text overlap with arXiv:2103.16047 
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Modality Fusion Network and Personalized Attention in Momentary Stress Detection in the Wild


Jul 21, 2021
Han Yu, Thomas Vaessen, Inez Myin-Germeys, Akane Sano

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Forecasting Health and Wellbeing for Shift Workers Using Job-role Based Deep Neural Network


Jun 22, 2021
Han Yu, Asami Itoh, Ryota Sakamoto, Motomu Shimaoka, Akane Sano

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* In: Wireless Mobile Communication and Healthcare. MobiHealth 2020 
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Topological Pilot Assignment in Large-Scale Distributed MIMO Networks


May 26, 2021
Han Yu, Xinping Yi, Giuseppe Caire

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Downlink Precoding for DP-UPA FDD Massive MIMO via Multi-Dimensional Active Channel Sparsification


Apr 27, 2021
Han Yu, Xinping Yi, Giuseppe Caire

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Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection


Apr 19, 2021
Xu Guo, Boyang Li, Han Yu, Chunyan Miao

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* 14 pages, 5 figures, NAACL conference 
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Noise-resistant Deep Metric Learning with Ranking-based Instance Selection


Apr 12, 2021
Chang Liu, Han Yu, Boyang Li, Zhiqi Shen, Zhanning Gao, Peiran Ren, Xuansong Xie, Lizhen Cui, Chunyan Miao

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* Accepted by CVPR 2021 
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HYDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks


Mar 01, 2021
Yuanyuan Chen, Boyang Li, Han Yu, Pengcheng Wu, Chunyan Miao

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Towards Personalized Federated Learning


Mar 01, 2021
Alysa Ziying Tan, Han Yu, Lizhen Cui, Qiang Yang

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Privacy and Robustness in Federated Learning: Attacks and Defenses


Dec 07, 2020
Lingjuan Lyu, Han Yu, Xingjun Ma, Lichao Sun, Jun Zhao, Qiang Yang, Philip S. Yu

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* arXiv admin note: text overlap with arXiv:2003.02133; text overlap with arXiv:1911.11815 by other authors 
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Federated Crowdsensing: Framework and Challenges


Nov 06, 2020
Leye Wang, Han Yu, Xiao Han

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SCNet: A Neural Network for Automated Side-Channel Attack


Aug 02, 2020
Guanlin Li, Chang Liu, Han Yu, Yanhong Fan, Libang Zhang, Zongyue Wang, Meiqin Wang

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Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention


Jun 15, 2020
Ce Ju, Ruihui Zhao, Jichao Sun, Xiguang Wei, Bo Zhao, Yang Liu, Hongshan Li, Tianjian Chen, Xinwei Zhang, Dashan Gao, Ben Tan, Han Yu, Yuan Jin

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* 4 pages, 3 figures, 1 table, Accepted for Workshop on Federated Learning for Data Privacy and Confidentiality in Conjunction with IJCAI 2020 (FL-IJCAI'20) 
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Threats to Federated Learning: A Survey


Mar 04, 2020
Lingjuan Lyu, Han Yu, Qiang Yang

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* 7 pages, 4 figures, 2 tables 
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FedCoin: A Peer-to-Peer Payment System for Federated Learning


Feb 26, 2020
Yuan Liu, Shuai Sun, Zhengpeng Ai, Shuangfeng Zhang, Zelei Liu, Han Yu

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* 7 pages, 6 figures,21 references 
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Multi-Participant Multi-Class Vertical Federated Learning


Jan 30, 2020
Siwei Feng, Han Yu

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FOCUS: Dealing with Label Quality Disparity in Federated Learning


Jan 29, 2020
Yiqiang Chen, Xiaodong Yang, Xin Qin, Han Yu, Biao Chen, Zhiqi Shen

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* 7 pages 
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FedVision: An Online Visual Object Detection Platform Powered by Federated Learning


Jan 17, 2020
Yang Liu, Anbu Huang, Yun Luo, He Huang, Youzhi Liu, Yuanyuan Chen, Lican Feng, Tianjian Chen, Han Yu, Qiang Yang

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Advances and Open Problems in Federated Learning


Dec 10, 2019
Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Keith Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaid Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konečný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao

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Reviewing and Improving the Gaussian Mechanism for Differential Privacy


Dec 07, 2019
Jun Zhao, Teng Wang, Tao Bai, Kwok-Yan Lam, Zhiying Xu, Shuyu Shi, Xuebin Ren, Xinyu Yang, Yang Liu, Han Yu

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* 23 Pages 
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Transfer Learning with Dynamic Distribution Adaptation


Sep 17, 2019
Jindong Wang, Yiqiang Chen, Wenjie Feng, Han Yu, Meiyu Huang, Qiang Yang

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* ACM Transactions on Intelligent Systems and Technology (ACM TIST) 2019 
 * Accepted to ACM Transactions on Intelligent Systems and Technology (ACM TIST) 2019, 25 pages. arXiv admin note: text overlap with arXiv:1807.07258 
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Privacy-preserving Crowd-guided AI Decision-making in Ethical Dilemmas


Jun 04, 2019
Teng Wang, Jun Zhao, Han Yu, Jinyan Liu, Xinyu Yang, Xuebin Ren, Shuyu Shi

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* 11pages 
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Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach


May 16, 2019
Jiawen Kang, Zehui Xiong, Dusit Niyato, Han Yu, Ying-Chang Liang, Dong In Kim

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* submitted to the conference for potential publication 
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