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Luca Saglietti
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2020 – today
- 2024
- [c7]Stefano Sarao Mannelli, Yaraslau Ivashinka, Andrew M. Saxe, Luca Saglietti:
Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks. ICML 2024 - [i16]Elizaveta Demyanenko, Christoph Feinauer, Enrico M. Malatesta, Luca Saglietti:
The twin peaks of learning neural networks. CoRR abs/2401.12610 (2024) - [i15]Stefano Sarao Mannelli, Yaraslau Ivashinka, Andrew M. Saxe, Luca Saglietti:
Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks. CoRR abs/2406.01589 (2024) - [i14]Damien Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala, Lenka Zdeborová:
The phase diagram of compressed sensing with ℓ0-norm regularization. CoRR abs/2408.08319 (2024) - [i13]Jerome Garnier-Brun, Marc Mézard, Emanuele Moscato, Luca Saglietti:
How transformers learn structured data: insights from hierarchical filtering. CoRR abs/2408.15138 (2024) - 2023
- [c6]Damien Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala
, Lenka Zdeborová:
Compressed sensing with ℓ0-norm: statistical physics analysis & algorithms for signal recovery. ITW 2023: 323-328 - [i12]Federica Gerace, Diego Doimo, Stefano Sarao Mannelli, Luca Saglietti, Alessandro Laio:
Optimal transfer protocol by incremental layer defrosting. CoRR abs/2303.01429 (2023) - [i11]Damien Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala
Compressed sensing with l0-norm: statistical physics analysis and algorithms for signal recovery. CoRR abs/2304.12127 (2023) - [i10]Brandon Livio Annesi, Clarissa Lauditi, Carlo Lucibello, Enrico M. Malatesta, Gabriele Perugini, Fabrizio Pittorino, Luca Saglietti:
The star-shaped space of solutions of the spherical negative perceptron. CoRR abs/2305.10623 (2023) - 2022
- [j3]Federica Gerace
Probing transfer learning with a model of synthetic correlated datasets. Mach. Learn. Sci. Technol. 3(1): 15030 (2022) - [c5]Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe:
An Analytical Theory of Curriculum Learning in Teacher-Student Networks. NeurIPS 2022 - [i9]Stefano Sarao Mannelli, Federica Gerace, Negar Rostamzadeh, Luca Saglietti:
Inducing bias is simpler than you think. CoRR abs/2205.15935 (2022) - 2021
- [j2]Hugo Cui
Large deviations in the perceptron model and consequences for active learning. Mach. Learn. Sci. Technol. 2(4): 45001 (2021) - [c4]Luca Saglietti, Lenka Zdeborová:
Solvable Model for Inheriting the Regularization through Knowledge Distillation. MSML 2021: 809-846 - [i8]Federica Gerace, Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe, Lenka Zdeborová:
Probing transfer learning with a model of synthetic correlated datasets. CoRR abs/2106.05418 (2021) - [i7]Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe:
An Analytical Theory of Curriculum Learning in Teacher-Student Networks. CoRR abs/2106.08068 (2021) - 2020
- [c3]Hugo Cui, Luca Saglietti, Lenka Zdeborová:
Large deviations for the perceptron model and consequences for active learning. MSML 2020: 390-430 - [i6]Luca Saglietti, Lenka Zdeborová:
Solvable Model for Inheriting the Regularization through Knowledge Distillation. CoRR abs/2012.00194 (2020)
2010 – 2019
- 2019
- [c2]Carlo Lucibello, Luca Saglietti, Yue M. Lu:
Generalized Approximate Survey Propagation for High-Dimensional Estimation. ICML 2019: 4173-4182 - [i5]Luca Saglietti, Yue M. Lu, Carlo Lucibello
Generalized Approximate Survey Propagation for High-Dimensional Estimation. CoRR abs/1905.05313 (2019) - [i4]Hugo Cui, Luca Saglietti, Lenka Zdeborová:
Large deviations for the perceptron model and consequences for active learning. CoRR abs/1912.03927 (2019) - 2018
- [b1]Luca Saglietti:
Out of equilibrium Statistical Physics of learning. Polytechnic University of Turin, Italy, 2018 - [c1]Francesco Paolo Casale, Adrian V. Dalca, Luca Saglietti, Jennifer Listgarten, Nicoló Fusi:
Gaussian Process Prior Variational Autoencoders. NeurIPS 2018: 10390-10401 - [i3]Francesco Paolo Casale, Adrian V. Dalca, Luca Saglietti, Jennifer Listgarten, Nicoló Fusi:
Gaussian Process Prior Variational Autoencoders. CoRR abs/1810.11738 (2018) - 2017
- [i2]Carlo Baldassi, Federica Gerace, Hilbert J. Kappen, Carlo Lucibello, Luca Saglietti, Enzo Tartaglione, Riccardo Zecchina:
On the role of synaptic stochasticity in training low-precision neural networks. CoRR abs/1710.09825 (2017) - 2016
- [j1]Carlo Baldassi
Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes. Proc. Natl. Acad. Sci. USA 113(48): E7655-E7662 (2016) - [i1]Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Alessandro Ingrosso, Carlo Lucibello
Unreasonable Effectiveness of Learning Neural Nets: Accessible States and Robust Ensembles. CoRR abs/1605.06444 (2016)
Coauthor Index
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