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Federated Learning 2020
- Qiang Yang, Lixin Fan, Han Yu
:
Federated Learning - Privacy and Incentive. Lecture Notes in Computer Science 12500, Springer 2020, ISBN 978-3-030-63075-1
Privacy
- Lingjuan Lyu, Han Yu
, Jun Zhao, Qiang Yang:
Threats to Federated Learning. 3-16 - Ligeng Zhu, Song Han:
Deep Leakage from Gradients. 17-31 - Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, Chang Liu, Chee Seng Chan, Qiang Yang:
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks. 32-50 - Ang Li, Huanrui Yang, Yiran Chen:
Task-Agnostic Privacy-Preserving Representation Learning via Federated Learning. 51-65 - Zhiyuan Dang
, Bin Gu
, Heng Huang
:
Large-Scale Kernel Method for Vertical Federated Learning. 66-80 - Lei Yu, Lingfei Wu:
Towards Byzantine-Resilient Federated Learning via Group-Wise Robust Aggregation. 81-92 - Ji Feng, Yi-Xuan Xu, Yong-Gang Wang, Yuan Jiang:
Federated Soft Gradient Boosting Machine for Streaming Data. 93-107 - Yiqiang Chen, Xiaodong Yang, Xin Qin, Han Yu
, Piu Chan, Zhiqi Shen:
Dealing with Label Quality Disparity in Federated Learning. 108-121
Incentive
- Yuan Liu, Zhengpeng Ai
, Shuai Sun, Shuangfeng Zhang, Zelei Liu, Han Yu
:
FedCoin: A Peer-to-Peer Payment System for Federated Learning. 125-138 - Shuyue Wei, Yongxin Tong
, Zimu Zhou, Tianshu Song:
Efficient and Fair Data Valuation for Horizontal Federated Learning. 139-152 - Tianhao Wang, Johannes Rausch, Ce Zhang, Ruoxi Jia, Dawn Song:
A Principled Approach to Data Valuation for Federated Learning. 153-167 - Zichen Chen, Zelei Liu, Kang Loon Ng, Han Yu
, Yang Liu, Qiang Yang:
A Gamified Research Tool for Incentive Mechanism Design in Federated Learning. 168-175 - Adam Richardson, Aris Filos-Ratsikas
, Boi Faltings:
Budget-Bounded Incentives for Federated Learning. 176-188 - Lingjuan Lyu, Xinyi Xu, Qian Wang
, Han Yu
:
Collaborative Fairness in Federated Learning. 189-204 - Mingshu Cong, Han Yu
, Xi Weng
, Siu-Ming Yiu:
A Game-Theoretic Framework for Incentive Mechanism Design in Federated Learning. 205-222
Applications
- Liu Yang, Ben Tan, Vincent W. Zheng, Kai Chen, Qiang Yang:
Federated Recommendation Systems. 225-239 - Guodong Long
, Yue Tan
, Jing Jiang
, Chengqi Zhang
:
Federated Learning for Open Banking. 240-254 - Trung Kien Dang
, Kwan Chet Tan, Mark Choo, Nicholas Lim, Jianshu Weng, Mengling Feng:
Building ICU In-hospital Mortality Prediction Model with Federated Learning. 255-268 - Xiawei Guo, Quanming Yao
, James T. Kwok, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction. 269-283
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