| Deep Leakage from Gradients L Zhu, S Han Federated Learning: Privacy and Incentive, 17–31, 2020 | 2460 | 2020 |
| Federated Learning for Open Banking G Long, Y Tan, J Jiang, C Zhang Federated Learning: Privacy and Incentive, 233–247, 2020 | 315 | 2020 |
| Collaborative Fairness in Federated Learning L Lyu, X Xu, Q Wang, H Yu Federated Learning: Privacy and Incentive, 185–199, 2020 | 224 | 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 | 212 | 2020 |
| Federated Recommendation Systems L Yang, B Tan, VW Zheng, K Chen, Q Yang Federated Learning: Privacy and Incentive, 218–232, 2020 | 211 | 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 | 134 | 2020 |
| Threats to Federated Learning L Lyu, H Yu, J Zhao, Q Yang Federated Learning: Privacy and Incentive, 1–14, 2020 | 108 | 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 | 103 | 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 | 65 | 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 | 56 | 2020 |
| Federated Learning: Privacy and Incentive Q Yang, L Fan, H Yu Springer International Publishing, Switzerland, 2020 | 45 | 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 | 31 | 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 | 16 | 2020 |
| Towards Byzantine-resilient Federated Learning via Group-wise Robust Aggregation L Yu, L Wu Federated Learning: Privacy and Incentive, 79–90, 2020 | 12 | 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 | 11 | 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 | 5 | 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 |
