11 citations · 24 across the 3 of their papers we have counts for
3 papers
FedVal: Different good or different bad in federated learning
Viktor Valadi, Xinchi Qiu, Pedro Porto Buarque de Gusmão +2
Federated learning (FL) systems are susceptible to attacks from malicious actors who might attempt to corrupt the training model through various poisoning attacks. FL also poses ne…
Protea: Client Profiling within Federated Systems using Flower
Wanru Zhao, Xinchi Qiu, Javier Fernandez-Marques +2
Federated Learning (FL) has emerged as a prospective solution that facilitates the training of a high-performing centralised model without compromising the privacy of users. While…
ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity
Xinchi Qiu, Javier Fernandez-Marques, Pedro PB Gusmao +3
When the available hardware cannot meet the memory and compute requirements to efficiently train high performing machine learning models, a compromise in either the training qualit…