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2 claims from 1 paper

1. Computer Science › Neural Networks and Applications

   Entropy landscape of solutions in the binary perceptron problem

   Huang, Wong and Kabashima · Journal of Physics A Mathematical and Theoretical · 2013

   The paper studies the geometry of the solution space of a binary perceptron through entropy landscapes, finding that the space shrinks with more constraints and shows both clustering and freezing.

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   1. UncheckedMean-field entropy calculations for the binary perceptron's solutions are matched by numerical simulations on single instances using message passing algorithms.“We evaluate the entropy at the annealed level as well as replica symmetric level and the mean field result is confirmed by the numerical simulations on single instances using the proposed message passing algorithms.”
   2. UncheckedIn the binary perceptron, the paper deduces that solutions to the learning problem can be both grouped in clusters and frozen in place.“From the second landscape of solution-pairs, we deduce the coexistence of clustering and freezing in the solution space.”