optimizer_adamax: Adamax optimizer

In SPOTMisc: Misc Extensions for the 'SPOT' Package

Adamax optimizer

Description

Adamax optimizer from Section 7 of the [Adam paper](https://arxiv.org/abs/1412.6980v8). It is a variant of Adam based on the infinity norm.

Usage

optimizer_adamax(
  learning_rate = 0.002,
  beta_1 = 0.9,
  beta_2 = 0.999,
  epsilon = NULL,
  decay = 0,
  clipnorm = NULL,
  clipvalue = NULL,
  ...
)

Arguments

learning_rate	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()'.
decay	float >= 0. Learning rate decay over each update.
clipnorm	Gradients will be clipped when their L2 norm exceeds this value.
clipvalue	Gradients will be clipped when their absolute value exceeds this value.
...	Unused, present only for backwards compatability

Note

To enable compatibility with the ranges of the learning rates of the other optimizers, the learning rate learning_rate is internally mapped to 2 * learning_rate. That is, a learning rat of 0.001 will be mapped to 0.002 (which is the default.)

See Also

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

SPOTMisc documentation built on Sept. 5, 2022, 5:06 p.m.