Scheduling for On-Board Federated Learning with Satellite Clusters

no code implementations • 14 Feb 2024 • Nasrin Razmi, Bho Matthiesen, Armin Dekorsy, Petar Popovski

Mega-constellations of small satellites have evolved into a source of massive amount of valuable data.

Federated Learning Scheduling

Scheduling for Ground-Assisted Federated Learning in LEO Satellite Constellations

no code implementations • 4 Jun 2022 • Nasrin Razmi, Bho Matthiesen, Armin Dekorsy, Petar Popovski

Distributed training of machine learning models directly on satellites in low Earth orbit (LEO) is considered.

Federated Learning Scheduling

Federated Learning in Satellite Constellations

no code implementations • 1 Jun 2022 • Bho Matthiesen, Nasrin Razmi, Israel Leyva-Mayorga, Armin Dekorsy, Petar Popovski

Federated learning (FL) has recently emerged as a distributed machine learning paradigm for systems with limited and intermittent connectivity.

BIG-bench Machine Learning Federated Learning

On-Board Federated Learning for Dense LEO Constellations

no code implementations • 24 Nov 2021 • Nasrin Razmi, Bho Matthiesen, Armin Dekorsy, Petar Popovski

Mega-constellations of small-size Low Earth Orbit (LEO) satellites are currently planned and deployed by various private and public entities.

Earth Observation Federated Learning

Ground-Assisted Federated Learning in LEO Satellite Constellations

no code implementations • 3 Sep 2021 • Nasrin Razmi, Bho Matthiesen, Armin Dekorsy, Petar Popovski

In Low Earth Orbit (LEO) mega constellations, there are relevant use cases, such as inference based on satellite imaging, in which a large number of satellites collaboratively train a machine learning model without sharing their local datasets.

Federated Learning