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Learning with noise and regularizers in multilayer neural networks
David Saad
, Sara A. Solla
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peer-review
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Dive into the research topics of 'Learning with noise and regularizers in multilayer neural networks'. Together they form a unique fingerprint.
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Keyphrases
Regularizer
100%
Multilayer Neural Network
100%
Noise Type
100%
Two-layer
100%
Learning with Noise
100%
Hidden Unit
100%
Input Vector
50%
Generalization Error
50%
Gradient-based Learning
50%
Online Gradient Descent
50%
Learning Process
50%
Teacher Networks
50%
Data Noise
50%
Gaussian Noise
50%
Learning Scenario
50%
Model Noise
50%
Student Networks
50%
Order Parameter
50%
Noisy Data
50%
Training Examples
50%
Engineering
Arbitrary Number
100%
Input Vector
50%
Gradient Descent
50%
Gaussian White Noise
50%
Physics
Neural Network
100%
Random Noise
100%