Learning from examples in large neural networks.

Learning from examples in large neural networks.

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http://www.wikidata.org/entity/Q52240112
Learning may need only a few bits of synaptic precision.Inferring hidden states in Langevin dynamics on large networks: Average case performance.Efficiency of quantum vs. classical annealing in nonconvex learning problems.Linear readout of object manifolds.Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses.A numerical study on learning curves in stochastic multilayer feedforward networks.Perturbative treatments and learning techniques.Bounds for predictive errors in the statistical mechanics of supervised learning.Scaling laws in learning of classification tasks.Stability of the replica-symmetric solution for a perceptron learning from examples.Learning in linear neural networks: The validity of the annealed approximation.Calculation of learning curves for inconsistent algorithms.Statistical mechanics of learning from examples.Learning unlearnable problems with perceptrons.Generalization performance of Bayes optimal classification algorithm for learning a perceptron.Neural network training without spurious minima
P2860

Learning from examples in large neural networks.

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http://www.wikidata.org/entity/Q52240112
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1990 nî lūn-bûn
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Learning from examples in large neural networks.
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Learning from examples in large neural networks.
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Learning from examples in large neural networks.
@en
Learning from examples in large neural networks.
@nl
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Learning from examples in large neural networks.
@en
Learning from examples in large neural networks.
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P1433
P1476
P2093
P2860
P304
P31
P356
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P478
P577
P698
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P1476
Learning from examples in large neural networks.
@en
P2093
P2860
P304
P31
P356
10.1103/PHYSREVLETT.65.1683
P407
P433
P478
P577
P698