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Found 2 papers, 1 papers with code
Source Separation and Depthwise Separable Convolutions for Computer Audition
Given recent advances in deep music source separation, we propose a feature representation method that combines source separation with a state-of-the-art representation learning technique that is suitably repurposed for computer audition (i. e. machine listening).
A Comparison of Machine Learning Algorithms Applied to American Legislature Polarization
We present a novel approach to the measurement of American state legislature polarization with an experimental comparison of three different machine learning algorithms.
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