338 citations · 1.3k across the 45 of their papers we have counts for
5 papers · 1 filter
A Framework for Parallel and Distributed Training of Neural Networks
Simone Scardapane, Paolo Di Lorenzo
The aim of this paper is to develop a general framework for training neural networks (NNs) in a distributed environment, where training data is partitioned over a set of agents tha…
Distributed Adaptive Learning of Graph Signals
P. Di Lorenzo, P. Banelli, S. Barbarossa +1
The aim of this paper is to propose distributed strategies for adaptive learning of signals defined over graphs. Assuming the graph signal to be bandlimited, the method enables dis…
Adaptive Least Mean Squares Estimation of Graph Signals
Paolo Di Lorenzo, Sergio Barbarossa, Paolo Banelli +1
The aim of this paper is to propose a least mean squares (LMS) strategy for adaptive estimation of signals defined over graphs. Assuming the graph signal to be band-limited, over a…
NEXT: In-Network Nonconvex Optimization
Paolo Di Lorenzo, Gesualdo Scutari
We study nonconvex distributed optimization in multi-agent networks with time-varying (nonsymmetric) connectivity. We introduce the first algorithmic framework for the distributed…
On the Graph Fourier Transform for Directed Graphs
Stefania Sardellitti, Sergio Barbarossa, Paolo Di Lorenzo
The analysis of signals defined over a graph is relevant in many applications, such as social and economic networks, big data or biological networks, and so on. A key tool for anal…