optimizer_nadam: Nesterov Adam optimizer

In dfalbel/keras: R Interface to 'Keras'

Description

Much like Adam is essentially RMSprop with momentum, Nadam is Adam RMSprop with Nesterov momentum.

Usage

optimizer_nadam(
  lr = 0.002,
  beta_1 = 0.9,
  beta_2 = 0.999,
  epsilon = NULL,
  schedule_decay = 0.004,
  clipnorm = NULL,
  clipvalue = NULL
)

Arguments

lr	float >= 0. Learning rate.
beta_1	The exponential decay rate for the 1st moment estimates. float, 0 < beta < 1. Generally close to 1.
beta_2	The exponential decay rate for the 2nd moment estimates. float, 0 < beta < 1. Generally close to 1.
epsilon	float >= 0. Fuzz factor. If NULL, defaults to k_epsilon().
schedule_decay	Schedule deacy.
clipnorm	Gradients will be clipped when their L2 norm exceeds this value.
clipvalue	Gradients will be clipped when their absolute value exceeds this value.

Details

Default parameters follow those provided in the paper. It is recommended to leave the parameters of this optimizer at their default values.

See Also

On the importance of initialization and momentum in deep learning.

Other optimizers: optimizer_adadelta(), optimizer_adagrad(), optimizer_adamax(), optimizer_adam(), optimizer_rmsprop(), optimizer_sgd()

dfalbel/keras documentation built on Nov. 27, 2019, 8:16 p.m.