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Luca Saglietti

Showing results (1-10 of 9) with videos related to

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Physical Review. E|April 16, 2022
Large deviations of semisupervised learning in the stochastic block modelHugo Cui, Luca Saglietti, Lenka Zdeborová
Journal of Statistical Mechanics (Online)|October 11, 2023
An analytical theory of curriculum learning in teacher-student networksLuca Saglietti, Stefano Sarao Mannelli, Andrew Saxe
Physical Review. E|September 16, 2025
Bias-inducing geometries: An exactly solvable data model with fairness implicationsStefano Sarao Mannelli, Federica Gerace, Negar Rostamzadeh, et al.
Physical Review. E|June 15, 2016
Learning may need only a few bits of synaptic precisionCarlo Baldassi, Federica Gerace, Carlo Lucibello, et al.
Physical Review Letters|October 3, 2015
Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete SynapsesCarlo Baldassi, Alessandro Ingrosso, Carlo Lucibello, et al.
Interface Focus|November 17, 2018
From statistical inference to a differential learning rule for stochastic neural networksLuca Saglietti, Federica Gerace, Alessandro Ingrosso, et al.
Physical Review Letters|July 14, 2018
Role of Synaptic Stochasticity in Training Low-Precision Neural NetworksCarlo Baldassi, Federica Gerace, Hilbert J Kappen, et al.
Proceedings of the National Academy of Sciences of the United States of America|November 19, 2016
Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemesCarlo Baldassi, Christian Borgs, Jennifer T Chayes, et al.
Physical Review Letters|December 15, 2023
Star-Shaped Space of Solutions of the Spherical Negative PerceptronBrandon Livio Annesi, Clarissa Lauditi, Carlo Lucibello, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Physical Review. E|April 16, 2022
Large deviations of semisupervised learning in the stochastic block modelHugo Cui, Luca Saglietti, Lenka Zdeborová
Journal of Statistical Mechanics (Online)|October 11, 2023
An analytical theory of curriculum learning in teacher-student networksLuca Saglietti, Stefano Sarao Mannelli, Andrew Saxe
Physical Review. E|September 16, 2025
Bias-inducing geometries: An exactly solvable data model with fairness implicationsStefano Sarao Mannelli, Federica Gerace, Negar Rostamzadeh, et al.
Physical Review. E|June 15, 2016
Learning may need only a few bits of synaptic precisionCarlo Baldassi, Federica Gerace, Carlo Lucibello, et al.
Physical Review Letters|October 3, 2015
Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete SynapsesCarlo Baldassi, Alessandro Ingrosso, Carlo Lucibello, et al.
Interface Focus|November 17, 2018
From statistical inference to a differential learning rule for stochastic neural networksLuca Saglietti, Federica Gerace, Alessandro Ingrosso, et al.
Physical Review Letters|July 14, 2018
Role of Synaptic Stochasticity in Training Low-Precision Neural NetworksCarlo Baldassi, Federica Gerace, Hilbert J Kappen, et al.
Proceedings of the National Academy of Sciences of the United States of America|November 19, 2016
Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemesCarlo Baldassi, Christian Borgs, Jennifer T Chayes, et al.
Physical Review Letters|December 15, 2023
Star-Shaped Space of Solutions of the Spherical Negative PerceptronBrandon Livio Annesi, Clarissa Lauditi, Carlo Lucibello, et al.
Pageof 1