optimizer_adadelta: Adadelta optimizer.

In SPOTMisc: Misc Extensions for the 'SPOT' Package

Adadelta optimizer.

Description

Adadelta optimizer as described in [ADADELTA: An Adaptive Learning Rate Method](https://arxiv.org/abs/1212.5701).

Usage

optimizer_adadelta(
  learning_rate = 0,
  rho = 0.95,
  epsilon = NULL,
  decay = 0,
  clipnorm = NULL,
  clipvalue = NULL,
  ...
)

Arguments

learning_rate	float >= 0. Learning rate.
rho	float >= 0. Decay factor.
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 enbale compatibility with the ranges of the learning rates of the other optimizers, the learning rate learning_rate is internally mapped to 1- learning_rate. That is, a learning rat of 0 will be mapped to 1 (which is the default.) It is recommended to leave the parameters of this optimizer at their default values.

See Also

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

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