OCD-FL: A Novel Communication-Efficient Peer Selection-based Decentralized Federated Learning

arXiv:2403.04037v1 Announce Type: new
Abstract: The conjunction of edge intelligence and the ever-growing Internet-of-Things (IoT) network heralds a new era of collaborative machine learning, with federated learning (FL) emerging as the most prominent paradigm. With the growing interest in these learning schemes, researchers started addressing some of their most fundamental limitations. Indeed, conventional FL with a central aggregator presents a single point of failure and a network bottleneck. To bypass this issue, decentralized FL where nodes collaborate in a peer-to-peer …

abstract arxiv collaborative communication cs.dc cs.lg decentralized edge edge intelligence federated learning intelligence internet iot limitations machine machine learning network novel paradigm peer researchers type