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Compact Encoding of Words for Efficient Character-level Convolutional Neural Networks Text Classification
This paper puts forward a new text to tensor representation that relies on information compression techniques to assign shorter codes to the most frequently used characters.
Averaged Hausdorff Approximations of Pareto Fronts based on Multiobjective Estimation of Distribution Algorithms
Therefore, we propose a postprocessing strategy which consists of applying the averaged Hausdorff indicator to the complete archive of generated solutions after optimization in order to select a uniformly distributed subset of nondominated solutions from the archive.
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