How to set adaptive learning rate for GradientDescentOptimizer?

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I am using TensorFlow to train a neural network. This is how I am initializing the GradientDescentOptimizer:

init = tf.initialize_all_variables()
sess = tf.Session()
sess.run(init)

mse        = tf.reduce_mean(tf.square(out - out_))
train_step = tf.train.GradientDescentOptimizer(0.3).minimize(mse)

The thing here is that I don"t know how to set an update rule for the learning rate or a decay value for that.

How can I use an adaptive learning rate here?

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