Type ProximalAdagradOptimizer
Namespace tensorflow.train
Parent Optimizer
Interfaces IProximalAdagradOptimizer
Optimizer that implements the Proximal Adagrad algorithm. See this [paper](http://papers.nips.cc/paper/3793-efficient-learning-using-forward-backward-splitting.pdf).
Methods
Properties
Public static methods
ProximalAdagradOptimizer NewDyn(object learning_rate, ImplicitContainer<T> initial_accumulator_value, ImplicitContainer<T> l1_regularization_strength, ImplicitContainer<T> l2_regularization_strength, ImplicitContainer<T> use_locking, ImplicitContainer<T> name)
Construct a new ProximalAdagrad optimizer.
Parameters
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objectlearning_rate - A `Tensor` or a floating point value. The learning rate.
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ImplicitContainer<T>initial_accumulator_value - A floating point value. Starting value for the accumulators, must be positive.
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ImplicitContainer<T>l1_regularization_strength - A float value, must be greater than or equal to zero.
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ImplicitContainer<T>l2_regularization_strength - A float value, must be greater than or equal to zero.
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ImplicitContainer<T>use_locking - If `True` use locks for update operations.
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ImplicitContainer<T>name - Optional name prefix for the operations created when applying gradients. Defaults to "Adagrad".