optimizer_adagrad
Adagrad optimizer.
Description
Adagrad optimizer as described in Adaptive Subgradient Methods for Online Learning and Stochastic Optimization.
Usage
optimizer_adagrad(
learning_rate = 0.01,
epsilon = NULL,
decay = 0,
clipnorm = NULL,
clipvalue = NULL,
...
) Arguments
| Arguments | Description |
|---|---|
| learning_rate | float >= 0. Learning rate. |
| 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
Other optimizers: optimizer_adadelta(), optimizer_adamax(), optimizer_adam(), optimizer_nadam(), optimizer_rmsprop(), optimizer_sgd()