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cs.LG2022★ 2 cited
SHED: A Newton-type algorithm for federated learning based on incremental Hessian eigenvector sharing
Nicolò Dal Fabbro, Subhrakanti Dey, Michele Rossi +1
There is a growing interest in the distributed optimization framework that goes under the name of Federated Learning (FL). In particular, much attention is being turned to FL scena…
cs.LG2017★ 29 cited
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…