8 citations · 9 across the 5 of their papers we have counts for
5 papers
Distributed clustering in partially overlapping feature spaces
Alessio Maritan, Luca Schenato
We introduce and address a novel distributed clustering problem where each participant has a private dataset containing only a subset of all available features, and some features a…
StaffPro: an LLM Agent for Joint Staffing and Profiling
Alessio Maritan
Large language model (LLM) agents integrate pre-trained LLMs with modular algorithmic components and have shown remarkable reasoning and decision-making abilities. In this work, we…
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…
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…
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…