Commit 98078146 authored by Jakob Knollmüller's avatar Jakob Knollmüller
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more text

parent 0a401ead
......@@ -23,6 +23,11 @@ class ADVIOptimizer(Minimizer):
"""Provide an implementation of an adaptive step-size sequence optimizer,
This stochastic optimizer keeps track of the evolution of the gradient over
the last steps to adaptively determine the step-size of the next update.
It is a variation of the Adam optimizer for Gaussian variational inference
and it allows to optimizer stochastic loss functions.
steps: int
......@@ -32,6 +37,7 @@ class ADVIOptimizer(Minimizer):
application to increase performance. Default: 1.
alpha: float between 0 and 1
The fraction of how much the current gradient impacts the momentum.
Lower values correspond to a longer memory.
tau: positive float
This quantity prevents division by zero.
epsilon: positive float
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