631 citations · 2.6k across the 22 of their papers we have counts for
6 papers · 1 filter
FedCVT: Semi-supervised Vertical Federated Learning with Cross-view Training
Yan Kang, Yang Liu, Xinle Liang
Federated learning allows multiple parties to build machine learning models collaboratively without exposing data. In particular, vertical federated learning (VFL) enables particip…
A VCG-based Fair Incentive Mechanism for Federated Learning
Mingshu Cong, Han Yu, Xi Weng +3
The enduring value of the Vickrey-Clarke-Groves (VCG) mechanism has been highlighted due to its adoption by Facebook ad auctions. Our research delves into its utility in the collab…
Backdoor attacks and defenses in feature-partitioned collaborative learning
Yang Liu, Zhihao Yi, Tianjian Chen
Since there are multiple parties in collaborative learning, malicious parties might manipulate the learning process for their own purposes through backdoor attacks. However, most o…
FedML: A Research Library and Benchmark for Federated Machine Learning
Chaoyang He, Songze Li, Jinhyun So +17
Federated learning (FL) is a rapidly growing research field in machine learning. However, existing FL libraries cannot adequately support diverse algorithmic development; inconsist…
FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data
Xinwei Zhang, Mingyi Hong, Sairaj Dhople +2
Federated Learning (FL) has become a popular paradigm for learning from distributed data. To effectively utilize data at different devices without moving them to the cloud, algorit…
Towards Utilizing Unlabeled Data in Federated Learning: A Survey and Prospective
Yilun Jin, Xiguang Wei, Yang Liu +1
Federated Learning (FL) proposed in recent years has received significant attention from researchers in that it can bring separate data sources together and build machine learning…