Weight initialization

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Random initialization

Normal distribution Continuous uniform distribution Independently Yoshua Bengio Independently and identically

16 related topics

History

Frank Rosenblatt Perceptrons Deep belief network Contrastive divergence Quasi-Newton method

8 related topics

Constant initialization

Multilayer perceptron Symmetry Residual connections LSTM ReLU

5 related topics

Miscellaneous

Hyperbolic tangent LeCun

2 related topics

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Overview

Deep learning
Neural network Neural network (machine learning)
Saturation Activation function
Backpropagation
Vanishing and exploding gradients Vanishing gradient problem
Convolutional neural networks Convolutional neural network
Kernels Kernel (image processing)

Constant initialization

Multilayer perceptron
Symmetry
Residual connections Residual neural network
LSTM Long short-term memory
ReLU Rectifier (neural networks)

Random initialization

Normal distribution
Continuous uniform distribution
Independently Independence (probability theory)
Yoshua Bengio
Independently and identically Independent and identically distributed random variables
Kaiming He
ReLU
Haar measure
Semi-orthogonal matrices Semi-orthogonal matrix
Deep linear network Deep linear network?action=edit&redlink=1
Unitary matrices Unitary matrix
VGG-19 VGGNet
Normalizations Normalization (machine learning)
Transformers Transformer (deep learning architecture)
Layer normalization
Sparse Sparse matrix

Miscellaneous

Hyperbolic tangent Hyperbolic functions
LeCun Yann LeCun

History

Frank Rosenblatt
Perceptrons Perceptron
Deep belief network
Contrastive divergence
Quasi-Newton method
Momentum gradient descent
Batch normalization
Momentum-based optimizers Adam optimizer

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Avg. degree1.95

Density0.045455

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Weight initialization

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related to Further reading · 24

Weight initialization → Aaron, Adaptive, Artificial Intelligence Review, Bartakke, Bengio, Business Media LLC, Cambridge, Courville, Deep, Goodfellow, Ian, ISBN, ISSN, June, Mass, Meenal, Mukul, Narkhede, Parameter Initialization Strategies, Prashant

related to history · 6

Weight initialization → An, Before, For, Frank Rosenblatt's, LeCun, Random

related to Constant initialization · 5

Weight initialization → Each, For, MLP, Specific, We

related to Fixup initialization · 5

Weight initialization → Fixup, In, Residual, These, VGG-19

is a · 1

Weight initialization → pre-training step of assigning initial values to these parameters.The choice of weight initialization method affects the speed of convergence

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Important terminology

initialization weight neural displaystyle network activation networks layer random deep weights initializing designed variance training method gradient parameters l-1 used

Entity relationships Subject–Predicate–Object triples

Subject	Predicate	Object	Confidence	Src
Weight initialization	is a	pre-training step of assigning initial values to these parameters.The choice of weight initialization method affects the speed of convergence	0.90	text
vanishing	instance of	Proper initialization is necessary for avoiding issues	0.80	text
exploding gradients	instance of	Proper initialization is necessary for avoiding issues	0.80	text
activation function saturation.Note that even though this article is titled	instance of	Proper initialization is necessary for avoiding issues	0.80	text
Weight initialization	related to Constant initialization	We	0.60	section
Weight initialization	related to Constant initialization	MLP	0.60	section
Weight initialization	related to Constant initialization	Specific	0.60	section
Weight initialization	related to Constant initialization	For	0.60	section
Weight initialization	related to Constant initialization	Each	0.60	section
Weight initialization	related to Fixup initialization	In	0.60	section
Weight initialization	related to Fixup initialization	VGG-19	0.60	section
Weight initialization	related to Fixup initialization	Residual	0.60	section

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Random initialization

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Constant initialization

Miscellaneous

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Overview

Constant initialization

Random initialization

Miscellaneous

History

Advanced semantic analysis

Map overview Semantic statistics

Weight initialization

How this topic connects Entity context

Weight initialization

Top relations

Important terminology Word statistics

Important terminology

Entity relationships Subject–Predicate–Object triples

Related concept clusters Concept neighborhoods

Connections between topic areas Semantic bridges