| CPC G06N 3/048 (2023.01) [G06N 3/088 (2013.01)] | 22 Claims |
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1. A system comprising:
persistent storage containing a representation of a neural-network-based encoder including an input layer and an output layer, wherein nodes of the output layer incorporate serialized activation functions, wherein the serialized activation functions for each of the nodes include a sigmoid function and a thresholding function, wherein the sigmoid function is applied to weighted outputs from nodes of a previous layer of the neural-network-based encoder, wherein the thresholding function is applied to outputs of the sigmoid function, wherein outputs of the thresholding function are binary, wherein the output layer was trained as a hidden layer of a neural-network-based auto-encoder, and wherein during training the thresholding function was replaced by a Beta function that was applied to a conductance hyper-parameter and respective outputs of the sigmoid function; and
one or more processors configured to:
introduce input to the input layer;
apply the serialized activation functions to the weighted outputs from the nodes of the previous layer; and
provide binary outputs from the output layer.
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