InfoWorld

The ‘toggle-away’ efficiencies: Cutting AI costs inside the training loop

You don't need the newest GPUs to save money on AI; simple tweaks like "smoke tests" and fixing data bottlenecks can slash ...
IEEE

Neuron Membership Inference Attack in Federated Learning for bit Scenarios

Abstract: Federated learning (FL) is a secure approach to protecting client data privacy by remaining data local. However, semi-honest central servers expose clients to the risk of membership ...
IEEE

FedBiF: Communication-Efficient Federated Learning via Bits Freezing

Abstract: Federated learning (FL) is an emerging distributed machine learning paradigm that enables collaborative model training without sharing local data. Despite its advantages, FL suffers from ...