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Monasson, Rémi, Zecchina, Riccardo (1995) Weight Space Structure and Internal Representations: A Direct Approach to Learning and Generalization in Multilayer Neural Networks. Physical Review Letters, 75 (12). 2432-2435 doi:10.1103/physrevlett.75.2432

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Reference TypeJournal (article/letter/editorial)
TitleWeight Space Structure and Internal Representations: A Direct Approach to Learning and Generalization in Multilayer Neural Networks
JournalPhysical Review Letters
AuthorsMonasson, RémiAuthor
Zecchina, RiccardoAuthor
Year1995 (September 18)Volume75
Issue12
PublisherAmerican Physical Society (APS)
DOIdoi:10.1103/physrevlett.75.2432Search in ResearchGate
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Mindat Ref. ID10565566Long-form Identifiermindat:1:5:10565566:6
GUID0
Full ReferenceMonasson, Rémi, Zecchina, Riccardo (1995) Weight Space Structure and Internal Representations: A Direct Approach to Learning and Generalization in Multilayer Neural Networks. Physical Review Letters, 75 (12). 2432-2435 doi:10.1103/physrevlett.75.2432
Plain TextMonasson, Rémi, Zecchina, Riccardo (1995) Weight Space Structure and Internal Representations: A Direct Approach to Learning and Generalization in Multilayer Neural Networks. Physical Review Letters, 75 (12). 2432-2435 doi:10.1103/physrevlett.75.2432
In(1995, September) Physical Review Letters Vol. 75 (12) American Physical Society (APS)

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Monasson, Rémi, Zecchina, Riccardo (1996) Weight Space Structure and Internal Representations: A Direct Approach to Learning and Generalization in Multilayer Neural Networks. Physical Review Letters, 76 (12). 2205 doi:10.1103/physrevlett.76.2205.3
Cocco, Simona, Monasson, Rémi, Zecchina, Riccardo (1996) Analytical and numerical study of internal representations in multilayer neural networks with binary weights. Physical Review E, 54 (1) 717-736 doi:10.1103/physreve.54.717
MONASSON, RÉMI, ZECCHINA, RICCARDO (1995) LEARNING AND GENERALIZATION THEORIES OF LARGE COMMITTEE-MACHINES. Modern Physics Letters B, 9. 1887-1897 doi:10.1142/s0217984995001868
Monasson, Rémi, Zecchina, Riccardo (1996) Entropy of theK-Satisfiability Problem. Physical Review Letters, 76 (21). 3881-3885 doi:10.1103/physrevlett.76.3881
Battista, Aldo, Monasson, Rémi (2020) Capacity-Resolution Trade-Off in the Optimal Learning of Multiple Low-Dimensional Manifolds by Attractor Neural Networks. Physical Review Letters, 124 (4). doi:10.1103/physrevlett.124.048302
Baldassi, Carlo, Ingrosso, Alessandro, Lucibello, Carlo, Saglietti, Luca, Zecchina, Riccardo (2015) Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses. Physical Review Letters, 115 (12). doi:10.1103/physrevlett.115.128101
Monasson, Rémi (1995) Structural Glass Transition and the Entropy of the Metastable States. Physical Review Letters, 75 (15). 2847-2850 doi:10.1103/physrevlett.75.2847
Monasson, Rémi, Zecchina, Riccardo (1997) Statistical mechanics of the randomK-satisfiability model. Physical Review E, 56 (2) 1357-1370 doi:10.1103/physreve.56.1357
Baldassi, Carlo, Malatesta, Enrico M., Zecchina, Riccardo (2019) Properties of the Geometry of Solutions and Capacity of Multilayer Neural Networks with Rectified Linear Unit Activations. Physical Review Letters, 123 (17). doi:10.1103/physrevlett.123.170602
Braunstein, Alfredo, Zecchina, Riccardo (2006) Learning by Message Passing in Networks of Discrete Synapses. Physical Review Letters, 96 (3). doi:10.1103/physrevlett.96.030201
Baldassi, Carlo, Lauditi, Clarissa, Malatesta, Enrico M., Perugini, Gabriele, Zecchina, Riccardo (2021) Unveiling the Structure of Wide Flat Minima in Neural Networks. Physical Review Letters, 127 (27) doi:10.1103/physrevlett.127.278301
 
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