Adagrad optimizer.

Adagrad optimizer as described in Adaptive Subgradient Methods for Online Learning and Stochastic Optimization.

optimizer_adagrad(lr = 0.01, epsilon = NULL, decay = 0,
  clipnorm = NULL, clipvalue = NULL)

Arguments

lr

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.

Note

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

See also