Search Results for author: Pietro Verzelli

Found 4 papers, 1 papers with code

Learn to Synchronize, Synchronize to Learn

no code implementations6 Oct 2020 Pietro Verzelli, Cesare Alippi, Lorenzo Livi

In recent years, the machine learning community has seen a continuous growing interest in research aimed at investigating dynamical aspects of both training procedures and machine learning models.

BIG-bench Machine Learning

Input-to-State Representation in linear reservoirs dynamics

no code implementations24 Mar 2020 Pietro Verzelli, Cesare Alippi, Lorenzo Livi, Peter Tino

Reservoir computing is a popular approach to design recurrent neural networks, due to its training simplicity and approximation performance.

Echo State Networks with Self-Normalizing Activations on the Hyper-Sphere

1 code implementation27 Mar 2019 Pietro Verzelli, Cesare Alippi, Lorenzo Livi

Finding such a region requires searching in hyper-parameter space in a sensible way: hyper-parameter configurations marginally outside such a region might yield networks exhibiting fully developed chaos, hence producing unreliable computations.

A characterization of the Edge of Criticality in Binary Echo State Networks

no code implementations3 Oct 2018 Pietro Verzelli, Lorenzo Livi, Cesare Alippi

Echo State Networks (ESNs) are simplified recurrent neural network models composed of a reservoir and a linear, trainable readout layer.

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