CPC G06F 18/211 (2023.01) [G06F 18/214 (2023.01); G06F 18/22 (2023.01); G06F 21/34 (2013.01); G06N 3/08 (2013.01); G06V 10/40 (2022.01); G06V 10/74 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 40/172 (2022.01)] | 23 Claims |
1. A processor-implemented method, the method comprising:
extracting feature data from input data using a first portion of a neural network;
generating compressed representation data of the extracted feature data by dropping a feature value from the extracted feature data at a drop layer of the neural network based on a drop probability corresponding to the feature value; and
indicating an inference result from the compressed representation data using a second portion of the neural network,
wherein the generating of the compressed representation data comprises determining whether to drop each feature value of the feature data based on a binomial distribution function with a drop probability corresponding to each feature value.
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