3 papers
Coded Task Offloading for Fluid Computing: A Privacy-Aware Approach under D2D Networks
Diego Cajaraville-Aboy, Manuel Fernández-Veiga, Ana Fernández-Vilas +1
Fluid Computing aims to support distributed applications execution across heterogeneous cloud, edge, and device resources, motivating task execution mechanisms that adapt to dynami…
Privacy-Preserving and Verifiable Approximate Distributed Coded Computing
Xavier Martínez-Luaña, Alba Gude-Santos, Manuel Fernández-Veiga +1
Distributed machine learning enables collaborative model training without centralizing data, but it also exposes learning processes to privacy leakage and malicious manipulation. E…
Byzantine-Robust Aggregation for Securing Decentralized Federated Learning
Diego Cajaraville-Aboy, Ana Fernández-Vilas, Rebeca P. Díaz-Redondo +1
Federated Learning (FL) emerges as a distributed machine learning approach that addresses privacy concerns by training AI models locally on devices. Decentralized Federated Learnin…