A library for performing constrained optimization in TensorFlow
TensorFlow Constrained Optimization (TFCO) is a library for optimizing inequality-constrained problems in TensorFlow.
In the most general case, both the objective function and the constraints are
Tensors, giving users the maximum amount of flexibility in
specifying their optimization problems. Constructing these
Tensors can be
cumbersome, so we also provide helper functions to make it easy to construct
constrained optimization problems based on rates, i.e. proportions of the
training data on which some event occurs (e.g. the error rate, true positive
rate, recall, etc).
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