8 citations · 9 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
FedZeN: Towards superlinear zeroth-order federated learning via incremental Hessian estimation
Alessio Maritan, Subhrakanti Dey, Luca Schenato
Federated learning is a distributed learning framework that allows a set of clients to collaboratively train a model under the orchestration of a central server, without sharing ra…
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…