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tensorflowbackpropagation

use resilient propagation on tensorflow

is there a way to use resilient propagation on Tensorflow? I know there are a number of back propagation strategies. Is there one that is close to rPorp? Can I insert my own implementation of resilient propagation?

Solution

  • There is no rprop implementation in tensorflow, although it would be fairly trivial to create one. You could create one by writing an op, or directly in python by combining ops.

    There is an RMSProp which is a different thing.

    Note that RProp doesn't work well with stochastic updates. The batch sizes would have to be very large for it to work.