no code implementations • 13 May 2023 • Alessio Maritan, Ganesh Sharma, Luca Schenato, Subhrakanti Dey
This paper considers the problem of distributed multi-agent learning, where the global aim is to minimize a sum of local objective (empirical loss) functions through local optimization and information exchange between neighbouring nodes.