Luca Saglietti

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Carlo LucibelloAssistant Professor, Bocconi UniversityVerified email at unibocconi.it
Carlo BaldassiBocconi University; ELLIS scholarVerified email at unibocconi.it
Riccardo Zecchinaprofessor, theoretical physics, Bocconi UniversityVerified email at unibocconi.it
Federica GeraceScuola Internazionale Superiore di Studi Avanzati - SISSAVerified email at sissa.it
Alessandro IngrossoAssistant Professor, Radboud UniversityVerified email at donders.ru.nl
Stefano SARAO MANNELLIAssistant Professor, DSAI CSE, Chalmers University of Technology and Gothenburg UniversityVerified email at chalmers.se
Lenka ZdeborováEPFL, SwitzerlandVerified email at epfl.ch
Andrew SaxeProfessor, Gatsby Unit & Sainsbury Wellcome Centre, UCLVerified email at ucl.ac.uk
Jennifer ChayesProfessor, UC BerkeleyVerified email at jenniferchayes.com
Francesco Paolo CasaleHelmholtz Pioneer Campus, Institute of AI for Health, Helmholtz Zentrum MünchenVerified email at helmholtz-muenchen.de
Nicolò FusiPartner Researcher, Microsoft ResearchVerified email at microsoft.com
Adrian V DalcaHarvard Medical School & Massachusetts Institute of TechnologyVerified email at mit.edu
Jennifer ListgartenProfessor, UC Berkeley EECS and Center for Computational BiologyVerified email at berkeley.edu
Enrico M. MalatestaAssistant Professor, Bocconi UniversityVerified email at unibocconi.it
Hugo CuiPostdoctoral fellow, Harvard CMSAVerified email at fas.harvard.edu
Hilbert Johan KappenRadboud UniversityVerified email at science.ru.nl
Enzo TartaglioneAssociate Professor, Télécom Paris, Institut Polytechnique de ParisVerified email at telecom-paris.fr
Clarissa LauditiPostdoctoral Fellow, Harvard UniversityVerified email at seas.harvard.edu
Fabrizio PittorinoPolitecnico di MilanoVerified email at polimi.it
Florent KrzakalaÉcole polytechnique fédérale de LausanneVerified email at epfl.ch

Luca Saglietti

Bocconi University - Computing Sciences

Verified email at unibocconi.it - Homepage

Statistical Physics Machine Learning


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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	203	2016
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	166	2015
Gaussian process prior variational autoencoders FP Casale, A Dalca, L Saglietti, J Listgarten, N Fusi Advances in neural information processing systems 31, 2018	146	2018
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	66	2016
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	37	2016
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	35	2022
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	28	2022
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	27	2018
Solvable model for inheriting the regularization through knowledge distillation L Saglietti, L Zdeborová Mathematical and Scientific Machine Learning, 809-846, 2022	22	2022
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	16	2023
Generalized approximate survey propagation for high-dimensional estimation C Lucibello, L Saglietti, Y Lu International Conference on Machine Learning, 4173-4182, 2019	12	2019
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	7	2021
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	7	2018
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	7	2018
How transformers learn structured data: insights from hierarchical filtering J Garnier-Brun, M Mézard, E Moscato, L Saglietti arXiv preprint arXiv:2408.15138, 2024	3	2024
Compressed sensing with ℓ₀-norm: statistical physics analysis & algorithms for signal recovery D Barbier, C Lucibello, L Saglietti, F Krzakala, L Zdeborová 2023 IEEE Information Theory Workshop (ITW), 323-328, 2023	3	2023
Large deviations for the perceptron model and consequences for active learning H Cui, L Saglietti, L Zdeborova Mathematical and Scientific Machine Learning, 390-430, 2020	3	2020
Unfair geometries: exactly solvable data model with fairness implications SS Mannelli, F Gerace, N Rostamzadeh, L Saglietti arXiv preprint arXiv:2205.15935, 2022	2	2022
Bias-inducing geometries: exactly solvable data model with fairness implications SS Mannelli, F Gerace, N Rostamzadeh, L Saglietti ICML 2024 Workshop on Geometry-grounded Representation Learning and …, 2024	1	2024
Optimal transfer protocol by incremental layer defrosting F Gerace, D Doimo, SS Mannelli, L Saglietti, A Laio arXiv preprint arXiv:2303.01429, 2023	1	2023

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