Analytical and numerical study of internal representations in multilayer neural networks with binary weights.
By Cocco, Monasson, Zecchina. 1996
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. @S1063-651X~96!01207-X#
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Citations in the corpus
- Entropy-SGD: biasing gradient descent into wide valleys (2016, background): “Local entropy, on the other hand, exploits wide minima which have been shown to exist in a variety of learning problems (Monasson & Zecchina, 1995; Cocco et al., 1996).”