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Qiang Yang
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

* arXiv admin note: text overlap with arXiv:2003.02133; text overlap with arXiv:1911.11815 by other authors 
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Rethinking Uncertainty in Deep Learning: Whether and How it Improves Robustness

Nov 27, 2020
Yilun Jin, Lixin Fan, Kam Woh Ng, Ce Ju, Qiang Yang


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FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning

Nov 25, 2020
Di Chai, Leye Wang, Kai Chen, Qiang Yang


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PrivNet: Safeguarding Private Attributes in Transfer Learning for Recommendation

Oct 16, 2020
Guangneng Hu, Qiang Yang

* Findings of EMNLP 2020 
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Two Sides of the Same Coin: White-box and Black-box Attacks for Transfer Learning

Aug 25, 2020
Yinghua Zhang, Yangqiu Song, Jian Liang, Kun Bai, Qiang Yang


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Protect, Show, Attend and Tell: Image Captioning Model with Ownership Protection

Aug 25, 2020
Jian Han Lim, Chee Seng Chan, Kam Woh Ng, Lixin Fan, Qiang Yang

* 9 pages 
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FedML: A Research Library and Benchmark for Federated Machine Learning

Jul 27, 2020
Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram, Salman Avestimehr

* We maintain the source code, documents, and user community at https://fedml.ai 
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Privacy Threats Against Federated Matrix Factorization

Jul 03, 2020
Dashan Gao, Ben Tan, Ce Ju, Vincent W. Zheng, Qiang Yang

* 6 pages, 2 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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Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks

Jun 23, 2020
Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, Chang Liu, Chee Seng Chan, Qiang Yang

* under review, 36 pages (updated Eq. 3 and Fig. 8) 
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SenWave: Monitoring the Global Sentiments under the COVID-19 Pandemic

Jun 18, 2020
Qiang Yang, Hind Alamro, Somayah Albaradei, Adil Salhi, Xiaoting Lv, Changsheng Ma, Manal Alshehri, Inji Jaber, Faroug Tifratene, Wei Wang, Takashi Gojobori, Carlos M. Duarte, Xin Gao, Xiangliang Zhang


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Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning

May 31, 2020
Wei Yang Bryan Lim, Jer Shyuan Ng, Zehui Xiong, Dusit Niyato, Cyril Leung, Chunyan Miao, Qiang Yang


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Network On Network for Tabular Data Classification in Real-world Applications

May 29, 2020
Yuanfei Luo, Hao Zhou, Weiwei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang


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Graph Random Neural Network

May 22, 2020
Wenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han, Huanbo Luan, Qian Xu, Qiang Yang, Jie Tang

* 12 pages, 22 figures 
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Fisher Deep Domain Adaptation

Mar 12, 2020
Yinghua Zhang, Yu Zhang, Ying Wei, Kun Bai, Yangqiu Song, Qiang Yang


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Threats to Federated Learning: A Survey

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

* 7 pages, 4 figures, 2 tables 
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A Survey towards Federated Semi-supervised Learning

Feb 26, 2020
Yilun Jin, Xiguang Wei, Yang Liu, Qiang Yang


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RPN: A Residual Pooling Network for Efficient Federated Learning

Jan 23, 2020
Anbu Huang, Yuanyuan Chen, Yang Liu, Tianjian Chen, Qiang Yang

* Accepted by the 24th European Conference on Artificial Intelligence (ECAI 2020) 
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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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A Communication Efficient Vertical Federated Learning Framework

Dec 27, 2019
Yang Liu, Yan Kang, Xinwei Zhang, Liping Li, Yong Cheng, Tianjian Chen, Mingyi Hong, 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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A Quasi-Newton Method Based Vertical Federated Learning Framework for Logistic Regression

Dec 04, 2019
Kai Yang, Tao Fan, Tianjian Chen, Yuanming Shi, Qiang Yang


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Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning

Oct 31, 2019
Zheng Li, Xin Li, Ying Wei, Lidong Bing, Yu Zhang, Qiang Yang


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L2RS: A Learning-to-Rescore Mechanism for Automatic Speech Recognition

Oct 25, 2019
Yuanfeng Song, Di Jiang, Xuefang Zhao, Qian Xu, Raymond Chi-Wing Wong, Lixin Fan, Qiang Yang

* 5 pages, 3 figures 
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Real-World Image Datasets for Federated Learning

Oct 14, 2019
Jiahuan Luo, Xueyang Wu, Yun Luo, Anbu Huang, Yunfeng Huang, Yang Liu, Qiang Yang


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Federated Transfer Reinforcement Learning for Autonomous Driving

Oct 14, 2019
Xinle Liang, Yang Liu, Tianjian Chen, Ming Liu, Qiang Yang


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