FedAds: A Benchmark for Privacy-Preserving CVR Estimation with Vertical Federated Learning

no code implementations • 15 May 2023 • Penghui Wei, Hongjian Dou, Shaoguo Liu, Rongjun Tang, Li Liu, Liang Wang, Bo Zheng

We introduce FedAds, the first benchmark for CVR estimation with vFL, to facilitate standardized and systematical evaluations for vFL algorithms.

Privacy Preserving Vertical Federated Learning

Data-free Backdoor Removal based on Channel Lipschitzness

2 code implementations • 5 Aug 2022 • Runkai Zheng, Rongjun Tang, Jianze Li, Li Liu

Pruning these channels was then shown to be effective in mitigating the backdoor behaviors.