Uses of Package
org.nd4j.linalg.learning.config

Packages that use org.nd4j.linalg.learning.config

Package	Description
org.nd4j.linalg.learning
org.nd4j.linalg.learning.config

Classes in org.nd4j.linalg.learning.config used by org.nd4j.linalg.learning

Class and Description
AdaDelta http://www.matthewzeiler.com/pubs/googleTR2012/googleTR2012.pdf https://arxiv.org/pdf/1212.5701v1.pdf
AdaGrad Vectorized Learning Rate used per Connection Weight Adapted from: http://xcorr.net/2014/01/23/adagrad-eliminating-learning-rates-in-stochastic-gradient-descent/ See also http://cs231n.github.io/neural-networks-3/#ada
Adam The Adam updater.
AdaMax The AdaMax updater, a variant of Adam.
AMSGrad The AMSGrad updater Reference: On the Convergence of Adam and Beyond - https://openreview.net/forum?id=ryQu7f-RZ
IUpdater IUpdater interface: used for configuration and instantiation of updaters - both built-in and custom. Note that the actual implementations for updaters are in GradientUpdater
Nadam Setup and DynamicCustomOpsBuilder for Nadam updater.
Nesterovs Nesterov's momentum.
NoOp NoOp updater: gradient updater that makes no changes to the gradient
RmsProp RMS Prop updates:
Sgd SGD updater applies a learning rate only

Classes in org.nd4j.linalg.learning.config used by org.nd4j.linalg.learning.config

Class and Description
AdaDelta http://www.matthewzeiler.com/pubs/googleTR2012/googleTR2012.pdf https://arxiv.org/pdf/1212.5701v1.pdf
AdaGrad Vectorized Learning Rate used per Connection Weight Adapted from: http://xcorr.net/2014/01/23/adagrad-eliminating-learning-rates-in-stochastic-gradient-descent/ See also http://cs231n.github.io/neural-networks-3/#ada
Adam The Adam updater.
AMSGrad The AMSGrad updater Reference: On the Convergence of Adam and Beyond - https://openreview.net/forum?id=ryQu7f-RZ
IUpdater IUpdater interface: used for configuration and instantiation of updaters - both built-in and custom. Note that the actual implementations for updaters are in GradientUpdater
Nadam Setup and DynamicCustomOpsBuilder for Nadam updater.
Nesterovs Nesterov's momentum.
NoOp NoOp updater: gradient updater that makes no changes to the gradient
RmsProp RMS Prop updates:
Sgd SGD updater applies a learning rate only