Information Theory, Compression Bounds, Feature Learning, Neural Networks
DRIFT: Data Reduction via Informative Feature Transformation- Generalization Begins Before Deep Learning starts
arxiv.org·12h
ML in the Home
blog.raymond.burkholder.net·1d
h-calibration: Rethinking Classifier Recalibration with Probabilistic Error-Bounded Objective
arxiv.org·1d
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