Deep Learning Seminar

"Automatic Transformation of Empirical Data Distribution as an Experimental Pre-Processing Step for Neural Networks"

Harar, Pavol

In this talk we introduce the Redistributor. A direct algorithm for automatic transformation of data from arbitrary empirical source distribution into chosen target distribution. The method is based on approximation of source cumulative distribution function and is suitable also for machine learning scenarios. Transformation is continuous, piecewise smooth, monotonic and invertible. We demonstrate its usage on mel-spectrogram data used to train a neural network.
http://pavol.harar.eu/

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