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math.OC2023
Network-GIANT: Fully distributed Newton-type optimization via harmonic Hessian consensus
Alessio Maritan, Ganesh Sharma, Luca Schenato +1
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 optimiza…
math.OC2023★ 8 cited
ZO-JADE: Zeroth-order Curvature-Aware Multi-Agent Convex Optimization
Alessio Maritan, Luca Schenato
In this work we address the problem of convex optimization in a multi-agent setting where the objective is to minimize the mean of local cost functions whose derivatives are not av…