Deep Leakage from Gradients L Zhu, S Han Federated Learning: Privacy and Incentive, 17–31, 2020 | 2334 | 2020 |
Federated Learning for Open Banking G Long, Y Tan, J Jiang, C Zhang Federated Learning: Privacy and Incentive, 233–247, 2020 | 293 | 2020 |
Collaborative Fairness in Federated Learning L Lyu, X Xu, Q Wang, H Yu Federated Learning: Privacy and Incentive, 185–199, 2020 | 205 | 2020 |
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 | 201 | 2020 |
Federated Recommendation Systems L Yang, B Tan, VW Zheng, K Chen, Q Yang Federated Learning: Privacy and Incentive, 218–232, 2020 | 195 | 2020 |
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 | 127 | 2020 |
Threats to Federated Learning L Lyu, H Yu, J Zhao, Q Yang Federated Learning: Privacy and Incentive, 1–14, 2020 | 101 | 2020 |
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 | 97 | 2020 |
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 | 59 | 2020 |
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 | 55 | 2020 |
Federated Learning: Privacy and Incentive Q Yang, L Fan, H Yu Springer International Publishing, Switzerland, 2020 | 41 | 2020 |
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 | 36 | 2020 |
Budget-bounded Incentives for Federated Learning A Richardson, A Filos-Ratsikas, B Faltings Federated Learning: Privacy and Incentive, 172–184, 2020 | 30 | 2020 |
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 | 14 | 2020 |
Towards Byzantine-resilient Federated Learning via Group-wise Robust Aggregation L Yu, L Wu Federated Learning: Privacy and Incentive, 79–90, 2020 | 11 | 2020 |
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 | 10 | 2020 |
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 | 5 | 2020 |
Large-Scale Kernel Method for Vertical Federated Learning Z Dang, B Gu, H Huang Federated Learning: Privacy and Incentive, 64–78, 2020 | 4 | 2020 |
Federated Soft Gradient Boosting Machine for Streaming Data J Feng, YX Wu, YGWY Jiang Federated Learning: Privacy and Incentive, 91–105, 2020 | 3 | 2020 |
Task-Agnostic Privacy-Preserving Representation Learning via Federated Learning A Li, H Yang, Y Chen Federated Learning: Privacy and Incentive, 49–63, 2020 | 2 | 2020 |