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Carlo Baldassi

Quantum Approximate Optimization Algorithm applied to the binary perceptron


Dec 19, 2021
Pietro Torta, Glen B. Mbeng, Carlo Baldassi, Riccardo Zecchina, Giuseppe E. Santoro

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* 14 pages, 9 figures 
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Learning through atypical ''phase transitions'' in overparameterized neural networks


Oct 01, 2021
Carlo Baldassi, Clarissa Lauditi, Enrico M. Malatesta, Rosalba Pacelli, Gabriele Perugini, Riccardo Zecchina

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* 28 pages, 14 figures 
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Unveiling the structure of wide flat minima in neural networks


Jul 02, 2021
Carlo Baldassi, Clarissa Lauditi, Enrico M. Malatesta, Gabriele Perugini, Riccardo Zecchina

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* 10 pages, 4 figures 
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Wide flat minima and optimal generalization in classifying high-dimensional Gaussian mixtures


Oct 27, 2020
Carlo Baldassi, Enrico M. Malatesta, Matteo Negri, Riccardo Zecchina

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* 18 pages, 4 figures. arXiv admin note: text overlap with arXiv:2006.07897 
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Ergodic Annealing


Aug 01, 2020
Carlo Baldassi, Fabio Maccheroni, Massimo Marinacci, Marco Pirazzini

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Entropic gradient descent algorithms and wide flat minima


Jun 14, 2020
Fabrizio Pittorino, Carlo Lucibello, Christoph Feinauer, Enrico M. Malatesta, Gabriele Perugini, Carlo Baldassi, Matteo Negri, Elizaveta Demyanenko, Riccardo Zecchina

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* 24 pages (main text: 8 pages) 
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Multialternative Neural Decision Processes


May 16, 2020
Carlo Baldassi, Simone Cerreia-Vioglio, Fabio Maccheroni, Massimo Marinacci, Marco Pirazzini


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Clustering of solutions in the symmetric binary perceptron


Nov 18, 2019
Carlo Baldassi, Riccardo Della Vecchia, Carlo Lucibello, Riccardo Zecchina

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Natural representation of composite data with replicated autoencoders


Sep 29, 2019
Matteo Negri, Davide Bergamini, Carlo Baldassi, Riccardo Zecchina, Christoph Feinauer

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* 11 pages, 4 figures 
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On the geometry of solutions and on the capacity of multi-layer neural networks with ReLU activations


Jul 17, 2019
Carlo Baldassi, Enrico M. Malatesta, Riccardo Zecchina

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* 11 pages, 3 figures 
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Shaping the learning landscape in neural networks around wide flat minima


May 21, 2019
Carlo Baldassi, Fabrizio Pittorino, Riccardo Zecchina

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* 46 pages (20 main text), 7 figures (v2 fixes fig. 1 and a few typos in formulas) 
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Recombinator-k-means: Enhancing k-means++ by seeding from pools of previous runs


May 01, 2019
Carlo Baldassi

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* 11 pages, 3 figures, 3 tables 
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On the role of synaptic stochasticity in training low-precision neural networks


Mar 20, 2018
Carlo Baldassi, Federica Gerace, Hilbert J. Kappen, Carlo Lucibello, Luca Saglietti, Enzo Tartaglione, Riccardo Zecchina

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* Phys. Rev. Lett. 120, 268103 (2018) 
 * 7 pages + 14 pages of supplementary material 
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Efficiency of quantum versus classical annealing in non-convex learning problems


Oct 16, 2017
Carlo Baldassi, Riccardo Zecchina

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* Proceedings of the National Academy of Sciences Jan 2018, 201711456 
 * 31 pages, 10 figures 
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Parle: parallelizing stochastic gradient descent


Sep 10, 2017
Pratik Chaudhari, Carlo Baldassi, Riccardo Zecchina, Stefano Soatto, Ameet Talwalkar, Adam Oberman

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Entropy-SGD: Biasing Gradient Descent Into Wide Valleys


Apr 21, 2017
Pratik Chaudhari, Anna Choromanska, Stefano Soatto, Yann LeCun, Carlo Baldassi, Christian Borgs, Jennifer Chayes, Levent Sagun, Riccardo Zecchina

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* ICLR '17 
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Unreasonable Effectiveness of Learning Neural Networks: From Accessible States and Robust Ensembles to Basic Algorithmic Schemes


Oct 06, 2016
Carlo Baldassi, Christian Borgs, Jennifer Chayes, Alessandro Ingrosso, Carlo Lucibello, Luca Saglietti, Riccardo Zecchina

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* Proc. Natl. Acad. Sci. U.S.A. 113(48):E7655-E7662, 2016 
 * 31 pages (14 main text, 18 appendix), 12 figures (6 main text, 6 appendix) 
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Learning may need only a few bits of synaptic precision


May 27, 2016
Carlo Baldassi, Federica Gerace, Carlo Lucibello, Luca Saglietti, Riccardo Zecchina

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* Phys. Rev. E 93, 052313 (2016) 
 * 38 pages (main text: 16 pages), 5 figures; http://link.aps.org/doi/10.1103/PhysRevE.93.052313 
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Local entropy as a measure for sampling solutions in Constraint Satisfaction Problems


Feb 25, 2016
Carlo Baldassi, Alessandro Ingrosso, Carlo Lucibello, Luca Saglietti, Riccardo Zecchina

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* J. Stat. Mech. 2016 (2) 023301 
 * 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 
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Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses


Sep 18, 2015
Carlo Baldassi, Alessandro Ingrosso, Carlo Lucibello, Luca Saglietti, Riccardo Zecchina

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* Physical Review Letters, 15, 128101 (2015) url=http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.115.128101 
 * 11 pages, 4 figures (main text: 5 pages, 3 figures; Supplemental Material: 6 pages, 1 figure) 
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A Max-Sum algorithm for training discrete neural networks


Aug 13, 2015
Carlo Baldassi, Alfredo Braunstein

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* Journal of Statistical Mechanics: Theory and Experiment 2015, no. 8, P08008 
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Efficient supervised learning in networks with binary synapses


Jul 09, 2007
Carlo Baldassi, Alfredo Braunstein, Nicolas Brunel, Riccardo Zecchina

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* PNAS 104, 11079-11084 (2007) 
 * 10 pages, 4 figures 
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