Sufficiently Informative and Relevant Features: An Information-Theoretic and Fourier-Based Characterization
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DOI: 10.1109/tit.2022.3169998
Abstract: A fundamental challenge in learning is the presence of nonlinear redundancies and dependencies in the data. To address this, we propose a Fourier-based approach to characterize feature redundancies, in unsupervised learning, and feature-label dependencies, in… read more here.
Keywords: fourier based; sufficiently informative; fourier; feature ... See more keywords