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Latest revision as of 08:46, 30 August 2017
Problem
To properly train a neural network a large labeled dataset, however large datasets of labeled data are not always available. This paper covers a method of generating labeled data for neural network training.
Methodology
Future Work
These models scale linearly in proportion to the number of classes in the data sets. The number of evaluations could be reduced by truncating the posterior mass or by using error-correcting output codes.