Luca Saglietti

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 23

Top Topics

Variational Formulation

Signal Recovery

Active Learning

Top Venues

Mach. Learn. Sci. Technol.

Publications

Elizaveta Demyanenko, Christoph Feinauer, Enrico M. Malatesta, Luca Saglietti
The twin peaks of learning neural networks. CoRR (2024)
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 (2024)
D. Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala, Lenka Zdeborová
Compressed sensing with ℓ0-norm: statistical physics analysis & algorithms for signal recovery. ITW (2023)
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 (2023)
D. Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala, Lenka Zdeborová
Compressed sensing with l0-norm: statistical physics analysis and algorithms for signal recovery. CoRR (2023)
Federica Gerace, Diego Doimo, Stefano Sarao Mannelli, Luca Saglietti, Alessandro Laio
Optimal transfer protocol by incremental layer defrosting. CoRR (2023)
Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe
An Analytical Theory of Curriculum Learning in Teacher-Student Networks. NeurIPS (2022)
Federica Gerace, Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe, Lenka Zdeborová
Probing transfer learning with a model of synthetic correlated datasets. Mach. Learn. Sci. Technol. 3 (1) (2022)
Stefano Sarao Mannelli, Federica Gerace, Negar Rostamzadeh, Luca Saglietti
Inducing bias is simpler than you think. CoRR (2022)
Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe
An Analytical Theory of Curriculum Learning in Teacher-Student Networks. CoRR (2021)
Federica Gerace, Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe, Lenka Zdeborová
Probing transfer learning with a model of synthetic correlated datasets. CoRR (2021)
Luca Saglietti, Lenka Zdeborová
Solvable Model for Inheriting the Regularization through Knowledge Distillation. MSML (2021)
Hugo Cui, Luca Saglietti, Lenka Zdeborová
Large deviations in the perceptron model and consequences for active learning. Mach. Learn. Sci. Technol. 2 (4) (2021)
Luca Saglietti, Lenka Zdeborová
Solvable Model for Inheriting the Regularization through Knowledge Distillation. CoRR (2020)
Hugo Cui, Luca Saglietti, Lenka Zdeborová
Large deviations for the perceptron model and consequences for active learning. MSML (2020)
Luca Saglietti, Yue M. Lu, Carlo Lucibello
Generalized Approximate Survey Propagation for High-Dimensional Estimation. CoRR (2019)
Carlo Lucibello, Luca Saglietti, Yue M. Lu
Generalized Approximate Survey Propagation for High-Dimensional Estimation. ICML (2019)
Hugo Cui, Luca Saglietti, Lenka Zdeborová
Large deviations for the perceptron model and consequences for active learning. CoRR (2019)
Francesco Paolo Casale, Adrian V. Dalca, Luca Saglietti, Jennifer Listgarten, Nicoló Fusi
Gaussian Process Prior Variational Autoencoders. NeurIPS (2018)
Francesco Paolo Casale, Adrian V. Dalca, Luca Saglietti, Jennifer Listgarten, Nicoló Fusi
Gaussian Process Prior Variational Autoencoders. CoRR (2018)
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 (2017)
Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Alessandro Ingrosso, Carlo Lucibello, Luca Saglietti, Riccardo Zecchina
Unreasonable Effectiveness of Learning Neural Nets: Accessible States and Robust Ensembles. CoRR (2016)
Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Alessandro Ingrosso, Carlo Lucibello, Luca Saglietti, Riccardo Zecchina
Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes. Proc. Natl. Acad. Sci. USA 113 (48) (2016)