Adadelta optimizer as described in ADADELTA: An Adaptive Learning Rate Method.

optimizer_adadelta(
  learning_rate = 1,
  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

It is recommended to leave the parameters of this optimizer at their default values.

See also