93 citations · 375 across the 30 of their papers we have counts for
5 papers · 1 filter
Generalized gradient optimization over lossy networks for partition-based estimation
Marco Todescato, Nicoletta Bof, Guido Cavraro +2
We address the problem of distributed convex unconstrained optimization over networks characterized by asynchronous and possibly lossy communications. We analyze the case where the…
Distributed multi-agent Gaussian regression via finite-dimensional approximations
Gianluigi Pillonetto, Luca Schenato, Damiano Varagnolo
We consider the problem of distributedly estimating Gaussian processes in multi-agent frameworks. Each agent collects few measurements and aims to collaboratively reconstruct a com…
Newton-Raphson Consensus under asynchronous and lossy communications for peer-to-peer networks
Nicoletta Bof, Ruggero Carli, Giuseppe Notarstefano +2
In this work we study the problem of unconstrained convex-optimization in a fully distributed multi-agent setting which includes asynchronous computation and lossy communication. I…
Efficient Spatio-Temporal Gaussian Regression via Kalman Filtering
Marco Todescato, Andrea Carron, Ruggero Carli +2
In this work we study the non-parametric reconstruction of spatio-temporal dynamical Gaussian processes (GPs) via GP regression from sparse and noisy data. GPs have been mainly app…
Analysis of Newton-Raphson Consensus for multi-agent convex optimization under asynchronous and lossy communications
Ruggero Carli, Giuseppe Notarstefano, Luca Schenato +1
We extend a multi-agent convex-optimization algorithm named Newton-Raphson consensus to a network scenario that involves directed, asynchronous and lossy communications. We theoret…