about
Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes.Learning may need only a few bits of synaptic precision.Finite-size corrections to disordered Ising models on random regular graphs.Scaling hypothesis for the Euclidean bipartite matching problem.Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses.Anomalous finite size corrections in random field modelsFinite-size corrections to disordered systems on Erdös-Rényi random graphsLocal entropy as a measure for sampling solutions in constraint satisfaction problemsOne-dimensional disordered Ising models by replica and cavity methodsLoop expansion around the Bethe solution for the random magnetic field Ising ferromagnets at zero temperature
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P50
description
onderzoeker
@nl
researcher
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հետազոտող
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name
C Lucibello
@ast
C Lucibello
@en
C Lucibello
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C Lucibello
@nl
type
label
C Lucibello
@ast
C Lucibello
@en
C Lucibello
@es
C Lucibello
@nl
prefLabel
C Lucibello
@ast
C Lucibello
@en
C Lucibello
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C Lucibello
@nl
P106
P1153
55965462000
P31
P496
0000-0003-0837-9783