Learning may need only a few bits of synaptic precision.

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Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes.Efficiency of quantum vs. classical annealing in nonconvex learning problems.

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Learning may need only a few bits of synaptic precision.

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2016 nî lūn-bûn

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2016年の論文

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2016年学术文章

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Learning may need only a few bits of synaptic precision.

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Learning may need only a few bits of synaptic precision.

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Learning may need only a few bits of synaptic precision.

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Learning may need only a few bits of synaptic precision.

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Learning may need only a few bits of synaptic precision.

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Learning may need only a few bits of synaptic precision.

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P1476

Learning may need only a few bits of synaptic precision.

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Federica Gerace

http://www.w3.org/2001/XMLSchema#string

Luca Saglietti

http://www.w3.org/2001/XMLSchema#string

P2860

Graded bidirectional synaptic plasticity is composed of switch-like unitary events

Optimal information storage and the distribution of synaptic weights: perceptron versus Purkinje cell.

Efficient supervised learning in networks with binary synapses.

Gibbs states and the set of solutions of random constraint satisfaction problems.

Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses.

Origin of the computational hardness for learning with binary synapses.

Learning by message passing in networks of discrete synapses.

Learning from examples in large neural networks.

Constructing Free-Energy Approximations and Generalized Belief Propagation Algorithms

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scholarly article

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10.1103/PHYSREVE.93.052313

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English

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http://www.w3.org/2001/XMLSchema#string

P478

http://www.w3.org/2001/XMLSchema#string

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Riccardo Zecchina

Carlo Baldassi

C Lucibello

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2016-05-27T00:00:00Z

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27300916

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1602.04129

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Learning may need only a few bits of synaptic precision.

about

P2860

P2860

Learning may need only a few bits of synaptic precision.

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