arXiv · cond-mat/9604102
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 behaviour and the symmetry breaking transition are analyzed and the results are found to be in very good agreement with extended numerical simulations.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Simona Cocco, Remi Monasson, Riccardo Zecchina. 1996-04-16. Analytical and Numerical Study of Internal Representations in Multilayer Neural Networks with Binary Weights. https://doi.org/10.1103/physreve.54.717
Cite the original work for its findings. Save a collection to share your selection of sources.