… federated learning protocol, TEA-Fed, to solve these problems. With TEA-Fed, idle edge
devices … Considering that there may be a huge number of edge devices in edge computing, we …

… 4 THE ASTRAL SYSTEM In this section we present Astral, a federated learning framework
for bias mitigation. First, we define formally the problem of bias mitigation in FL in §4.1. Then, …

… 1) We propose a novel DHT-DCM for federated learning under the framework of edge
computing. It condenses the model parameters from a high-dimensional tensor space into a set of …

… apply it in general federated learning designed for industrial edge computing. In order to …
we can divide the federated learning into five steps: edge terminal computing, noise generation, …

… edge computing server includes three main components, namely Recurrent Long-term Capture
Network (RLCN) module, Attentive Mechanism Federated … Vertical Federated Learning (…

… learning model over distributed datasets while preserving the training data privacy. We
extend the application of federated learning … of Parked Vehicle assisted Edge Computing (PVEC) …

… federated learning through adaptive model pruning. Specifically, we adopt a structured model
pruning approach for federated learning … We then propose an MAB based online learning …

… With the advent of 5G, edge computing and federated learning have attracted … a federated
learning system that is more suitable for collaborative learning of discrete nodes in edge …

… edge computing server. Therefore, the local training system consists of two phrases: the
mobile training and the mobile edge computing … and performance of federated learning model, …

… computation costs in mobile edge devices. Moreover, among … edge devices while providing
strong privacy guarantees, we propose a mobile edge computing enabled federated learning …