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Federated Learning: Privacy and Incentive
Federated Learning: Privacy and Incentive
Springer International Publishing, Switzerland
Verified email at ntu.edu.sg - Homepage
Title
Cited by
Cited by
Year
Deep Leakage from Gradients
L Zhu, S Han
Federated Learning: Privacy and Incentive, 17–31, 2020
23342020
Federated Learning for Open Banking
G Long, Y Tan, J Jiang, C Zhang
Federated Learning: Privacy and Incentive, 233–247, 2020
2932020
Collaborative Fairness in Federated Learning
L Lyu, X Xu, Q Wang, H Yu
Federated Learning: Privacy and Incentive, 185–199, 2020
2052020
A Principled Approach to Data Valuation for Federated Learning
T Wang, J Rausch, C Zhang, R Jia, D Song
Federated Learning: Privacy and Incentive, 149–163, 2020
2012020
Federated Recommendation Systems
L Yang, B Tan, VW Zheng, K Chen, Q Yang
Federated Learning: Privacy and Incentive, 218–232, 2020
1952020
FedCoin: A Peer-to-Peer Payment System for Federated Learning
Y Liu, Z Ai, S Sun, S Zhang, Z Liu, H Yu
Federated Learning: Privacy and Incentive, 121–134, 2020
1272020
Threats to Federated Learning
L Lyu, H Yu, J Zhao, Q Yang
Federated Learning: Privacy and Incentive, 1–14, 2020
1012020
Dealing with Label Quality Disparity In Federated Learning
Y Chen, X Yang, X Qin, H Yu, P Chan, Z Shen
Federated Learning: Privacy and Incentive, 106–120, 2020
972020
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks
L Fan, KW Ng, C Ju, T Zhang, C Liu, CS Chan, Q Yang
Federated Learning: Privacy and Incentive, 30–48, 2020
592020
Efficient and Fair Data Valuation for Horizontal Federated Learning
S Wei, Y Tong, Z Zhou, T Song
Federated Learning: Privacy and Incentive, 135–148, 2020
552020
Federated Learning: Privacy and Incentive
Q Yang, L Fan, H Yu
Springer International Publishing, Switzerland, 2020
412020
A Game-Theoretic Framework for Incentive Mechanism Design in Federated Learning
M Cong, H Yu, X Weng, SM Yiu
Federated Learning: Privacy and Incentive, 200–217, 2020
362020
Budget-bounded Incentives for Federated Learning
A Richardson, A Filos-Ratsikas, B Faltings
Federated Learning: Privacy and Incentive, 172–184, 2020
302020
Building ICU In-hospital Mortality Prediction Model with Federated Learning
TK Dang, KC Tan, M Choo, N Lim, J Weng, M Feng
Federated Learning: Privacy and Incentive, 248–262, 2020
142020
Towards Byzantine-resilient Federated Learning via Group-wise Robust Aggregation
L Yu, L Wu
Federated Learning: Privacy and Incentive, 79–90, 2020
112020
A Gamified Research Tool for Incentive Mechanism Design in Federated Learning
Z Chen, Z Liu, KL Ng, H Yu, Y Liu, Q Yang
Federated Learning: Privacy and Incentive, 164–171, 2020
102020
Privacy-preserving Stacking with Application to Cross-organizational Diabetes Prediction
X Guo, Q Yao, J Kwok, W Tu, Y Chen, W Dai, Q Yang
Federated Learning: Privacy and Incentive, 263–277, 2020
52020
Large-Scale Kernel Method for Vertical Federated Learning
Z Dang, B Gu, H Huang
Federated Learning: Privacy and Incentive, 64–78, 2020
42020
Federated Soft Gradient Boosting Machine for Streaming Data
J Feng, YX Wu, YGWY Jiang
Federated Learning: Privacy and Incentive, 91–105, 2020
32020
Task-Agnostic Privacy-Preserving Representation Learning via Federated Learning
A Li, H Yang, Y Chen
Federated Learning: Privacy and Incentive, 49–63, 2020
22020
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