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Disambiguation of "Saglietti, Luca"

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Learning may need only a few bits of synaptic precision

, , , , and . (2016)cite arxiv:1602.04129Comment: 38 pages (main text: 16 pages), 5 figures; http://link.aps.org/doi/10.1103/PhysRevE.93.052313.
DOI: 10.1103/PhysRevE.93.052313

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Francesca Saglietti

Francesca Saglietti

Luca Rizzini

Luca Tranchini

Luca Tuninetti

 

Other publications of authors with the same name

Probing transfer learning with a model of synthetic correlated datasets., , , , and . CoRR, (2021)Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks., , , and . ICML, OpenReview.net, (2024)Unreasonable Effectiveness of Learning Neural Networks: From Accessible States and Robust Ensembles to Basic Algorithmic Schemes, , , , , , and . (2016)cite arxiv:1605.06444Comment: 31 pages (14 main text, 18 appendix), 12 figures (6 main text, 6 appendix).Local entropy as a measure for sampling solutions in Constraint Satisfaction Problems, , , , and . (2015)cite arxiv:1511.05634Comment: 46 pages (main text: 22), 7 figures. This is an author-created, un-copyedited version of an article published in Journal of Statistical Mechanics: Theory and Experiment. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at http://dx.doi.org/10.1088/1742-5468/2016/02/023301.Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses, , , , and . (2015)cite arxiv:1509.05753Comment: 11 pages, 4 figures (main text: 5 pages, 3 figures; Supplemental Material: 6 pages, 1 figure).An Analytical Theory of Curriculum Learning in Teacher-Student Networks., , and . NeurIPS, (2022)An Analytical Theory of Curriculum Learning in Teacher-Student Networks., , and . CoRR, (2021)Out of equilibrium Statistical Physics of learning.. Polytechnic University of Turin, Italy, (2018)base-search.net (ftpoltorinoiris:oai:iris.polito.it:11583/2710532).Learning may need only a few bits of synaptic precision, , , , and . (2016)cite arxiv:1602.04129Comment: 38 pages (main text: 16 pages), 5 figures; http://link.aps.org/doi/10.1103/PhysRevE.93.052313.Large deviations for the perceptron model and consequences for active learning., , and . MSML, volume 107 of Proceedings of Machine Learning Research, page 390-430. PMLR, (2020)