68 citations · 117 across the 5 of their papers we have counts for
5 papers
Probably Approximately Correct Federated Learning
Xiaojin Zhang, Anbu Huang, Lixin Fan +2
Federated learning (FL) is a new distributed learning paradigm, with privacy, utility, and efficiency as its primary pillars. Existing research indicates that it is unlikely to sim…
Dynamic backdoor attacks against federated learning
Anbu Huang
Federated Learning (FL) is a new machine learning framework, which enables millions of participants to collaboratively train machine learning model without compromising data privac…
FedVision: An Online Visual Object Detection Platform Powered by Federated Learning
Yang Liu, Anbu Huang, Yun Luo +7
Visual object detection is a computer vision-based artificial intelligence (AI) technique which has many practical applications (e.g., fire hazard monitoring). However, due to priv…
RPN: A Residual Pooling Network for Efficient Federated Learning
Anbu Huang, Yuanyuan Chen, Yang Liu +2
Federated learning is a distributed machine learning framework which enables different parties to collaboratively train a model while protecting data privacy and security. Due to m…
Real-World Image Datasets for Federated Learning
Jiahuan Luo, Xueyang Wu, Yun Luo +4
Federated learning is a new machine learning paradigm which allows data parties to build machine learning models collaboratively while keeping their data secure and private. While…