Luca Saglietti
Title
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Cited by
Year
Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes
C Baldassi, C Borgs, JT Chayes, A Ingrosso, C Lucibello, L Saglietti, ...
Proceedings of the National Academy of Sciences 113 (48), E7655-E7662, 2016
1012016
Subdominant dense clusters allow for simple learning and high computational performance in neural networks with discrete synapses
C Baldassi, A Ingrosso, C Lucibello, L Saglietti, R Zecchina
Physical review letters 115 (12), 128101, 2015
842015
Gaussian process prior variational autoencoders
FP Casale, A Dalca, L Saglietti, J Listgarten, N Fusi
Advances in Neural Information Processing Systems, 10369-10380, 2018
332018
Local entropy as a measure for sampling solutions in constraint satisfaction problems
C Baldassi, A Ingrosso, C Lucibello, L Saglietti, R Zecchina
Journal of Statistical Mechanics: Theory and Experiment 2016 (2), 023301, 2016
332016
Learning may need only a few bits of synaptic precision
C Baldassi, F Gerace, C Lucibello, L Saglietti, R Zecchina
Physical Review E 93 (5), 052313, 2016
212016
Role of synaptic stochasticity in training low-precision neural networks
C Baldassi, F Gerace, HJ Kappen, C Lucibello, L Saglietti, E Tartaglione, ...
Physical review letters 120 (26), 268103, 2018
202018
From statistical inference to a differential learning rule for stochastic neural networks
L Saglietti, F Gerace, A Ingrosso, C Baldassi, R Zecchina
Interface focus 8 (6), 20180033, 2018
52018
From inverse problems to learning: a statistical mechanics approach
C Baldassi, F Gerace, L Saglietti, R Zecchina
Journal of Physics: Conference Series 955, 012001, 2018
32018
Generalized approximate survey propagation for high-dimensional estimation
C Lucibello, L Saglietti, Y Lu
International Conference on Machine Learning, 4173-4182, 2019
22019
Generalized Approximate Survey Propagation for High-Dimensional Estimation: Supplementary Material
L Saglietti, Y Lu, C Lucibello
arXiv preprint arXiv:1905.05313, 0
1
Large deviations for the perceptron model and consequences for active learning
H Cui, L Saglietti, L Zdeborová
Mathematical and Scientific Machine Learning, 390-430, 2020
2020
Generalized Approximate Survey Propagation for High-Dimensional Estimation
L Saglietti, YM Lu, C Lucibello
arXiv preprint arXiv:1905.05313, 2019
2019
Out of Equilibrium Statistical Physics of Learning
L Saglietti
Politecnico di Torino, 2018
2018
Role of synaptic stochasticity in training low-precision neural networks Download PDF
C Baldassi, F Gerace, HJ Kappen, C Lucibello, L Saglietti, E Tartaglione, ...
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