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Luca Saglietti
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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
1862016
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
1472015
Gaussian process prior variational autoencoders
FP Casale, A Dalca, L Saglietti, J Listgarten, N Fusi
Advances in neural information processing systems 31, 2018
1202018
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
592016
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
322016
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
262018
Probing transfer learning with a model of synthetic correlated datasets
F Gerace, L Saglietti, SS Mannelli, A Saxe, L Zdeborová
Machine Learning: Science and Technology 3 (1), 015030, 2022
222022
Solvable model for inheriting the regularization through knowledge distillation
L Saglietti, L Zdeborová
Mathematical and Scientific Machine Learning, 809-846, 2022
182022
An analytical theory of curriculum learning in teacher-student networks
L Saglietti, S Mannelli, A Saxe
Advances in Neural Information Processing Systems 35, 21113-21127, 2022
162022
Generalized approximate survey propagation for high-dimensional estimation
C Lucibello, L Saglietti, Y Lu
International Conference on Machine Learning, 4173-4182, 2019
102019
Star-shaped space of solutions of the spherical negative perceptron
BL Annesi, C Lauditi, C Lucibello, EM Malatesta, G Perugini, F Pittorino, ...
Physical Review Letters 131 (22), 227301, 2023
72023
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
62018
From inverse problems to learning: a statistical mechanics approach
C Baldassi, F Gerace, L Saglietti, R Zecchina
Journal of Physics: Conference Series 955 (1), 012001, 2018
62018
Large deviations in the perceptron model and consequences for active learning
H Cui, L Saglietti, L Zdeborová
Machine Learning: Science and Technology 2 (4), 045001, 2021
42021
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
32020
Inducing bias is simpler than you think
SS Mannelli, F Gerace, N Rostamzadeh, L Saglietti
arXiv preprint arXiv:2205.15935, 2022
12022
Generalized Approximate Survey Propagation for High-Dimensional Estimation: Supplementary Material
L Saglietti, Y Lu, C Lucibello
arXiv preprint arXiv:1905.05313, 0
1
The twin peaks of learning neural networks
E Demyanenko, C Feinauer, EM Malatesta, L Saglietti
arXiv preprint arXiv:2401.12610, 2024
2024
Degradation Assessment for Prototypal Perovskite Photovoltaic Modules in Long Term Outdoor Experimental Campaign
G Aime, A Ciocia, G Malgaroli, S Narbey, L Saglietti, F Spertino
2023 IEEE International Conference on Environment and Electrical Engineering …, 2023
2023
The star-shaped space of solutions of the spherical negative perceptron
B Livio Annesi, C Lauditi, C Lucibello, EM Malatesta, G Perugini, ...
arXiv e-prints, arXiv: 2305.10623, 2023
2023
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