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- Carlo Baldassi, Christian Borgs, +4 authors Riccardo Zecchina
- Proceedings of the National Academy of Sciences…
- 2016

In artificial neural networks, learning from data is a computationally demanding task in which a large number of connection weights are iteratively tuned through stochastic-gradient-based heuristic… (More)

- Carlo Baldassi, Alessandro Ingrosso, Carlo Lucibello, Luca Saglietti, Riccardo Zecchina
- Physical review letters
- 2015

We show that discrete synaptic weights can be efficiently used for learning in large scale neural systems, and lead to unanticipated computational performance. We focus on the representative case of… (More)

- Carlo Baldassi, Federica Gerace, Carlo Lucibello, Luca Saglietti, Riccardo Zecchina
- Physical review. E
- 2016

Learning in neural networks poses peculiar challenges when using discretized rather then continuous synaptic states. The choice of discrete synapses is motivated by biological reasoning and… (More)

- Carlo Baldassi, Christian Borgs, +4 authors Riccardo Zecchina
- ArXiv
- 2016

Carlo Baldassi, 2 Christian Borgs, Jennifer Chayes, Alessandro Ingrosso, 2 Carlo Lucibello, 2 Luca Saglietti, 2 and Riccardo Zecchina 2, 4 Dept. Applied Science and Technology, Politecnico di Torino,… (More)

- Sergio Caracciolo, Carlo Lucibello, Giorgio Parisi, Gabriele Sicuro
- Physical review. E, Statistical, nonlinear, and…
- 2014

We propose a simple yet very predictive form, based on a Poisson's equation, for the functional dependence of the cost from the density of points in the Euclidean bipartite matching problem. This… (More)

U. Ferrari,1 C. Lucibello,2 F. Morone,2 G. Parisi,3 F. Ricci-Tersenghi,3 and T. Rizzo4 1Laboratoire de Physique Théorique de l’ENS, CNRS and UPMC, 24 rue Lhomond, F-75005 Paris, France 2Dipartimento… (More)

- Carlo Baldassi, Federica Gerace, +4 authors Riccardo Zecchina
- Physical review letters
- 2018

Stochasticity and limited precision of synaptic weights in neural network models are key aspects of both biological and hardware modeling of learning processes. Here we show that a neural network… (More)

- Carlo Lucibello, Giorgio Parisi, Gabriele Sicuro
- Physical review. E
- 2017

The matching problem is a notorious combinatorial optimization problem that has attracted for many years the attention of the statistical physics community. Here we analyze the Euclidean version of… (More)

Disordered systems are actively investigated in the statistical physics community, their presence being ubiquitous in material science, biology, finance, information theory. Even the most simple… (More)

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