Analytical and numerical study of internal representations in multilayer neural networks with binary weights

Simona Cocco; Rémi Monasson; Riccardo Zecchina

doi:10.1103/PhysRevE.54.717

Analytical and numerical study of internal representations in multilayer neural networks with binary weights

Simona Cocco
, Rémi Monasson
, Riccardo Zecchina

Sezione di Roma
Center for Atomic-scale Materials Physics (CAMP)
Politecnico di Torino

Research output: Contribution to journal › Article › peer-review

17 Citations (Scopus)

Abstract

We study the weight space structure of the parity machine with binary weights by deriving the distribution of volumes associated to the internal representations of the learning examples. The learning behavior and the symmetry breaking transition are analyzed and the results are found to be in very good agreement with the extended numerical simulations.

Original language	English
Pages (from-to)	717-736
Number of pages	20
Journal	Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
Volume	54
Issue number	1
DOIs	https://doi.org/10.1103/PhysRevE.54.717
Publication status	Published - 1 Jan 1996
Externally published	Yes

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10.1103/PhysRevE.54.717

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title = "Analytical and numerical study of internal representations in multilayer neural networks with binary weights",

abstract = "We study the weight space structure of the parity machine with binary weights by deriving the distribution of volumes associated to the internal representations of the learning examples. The learning behavior and the symmetry breaking transition are analyzed and the results are found to be in very good agreement with the extended numerical simulations.",

author = "Simona Cocco and R{\'e}mi Monasson and Riccardo Zecchina",

year = "1996",

month = jan,

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doi = "10.1103/PhysRevE.54.717",

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journal = "Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics",

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Analytical and numerical study of internal representations in multilayer neural networks with binary weights. / Cocco, Simona; Monasson, Rémi; Zecchina, Riccardo.
In: Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, Vol. 54, No. 1, 01.01.1996, p. 717-736.

Research output: Contribution to journal › Article › peer-review

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AB - We study the weight space structure of the parity machine with binary weights by deriving the distribution of volumes associated to the internal representations of the learning examples. The learning behavior and the symmetry breaking transition are analyzed and the results are found to be in very good agreement with the extended numerical simulations.

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DO - 10.1103/PhysRevE.54.717

M3 - Article

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SN - 1063-651X

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JF - Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics

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Analytical and numerical study of internal representations in multilayer neural networks with binary weights

Abstract

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