Web: http://arxiv.org/abs/2206.08014

June 17, 2022, 1:12 a.m. | Omer Kerem, Roi Weiss

stat.ML updates on arXiv.org arxiv.org

We study the close interplay between error and compression in the
non-parametric multiclass classification setting in terms of prototype learning
rules. We focus in particular on a close variant of a recently proposed
compression-based learning rule termed OptiNet. Beyond its computational
merits, this rule has been recently shown to be universally consistent in any
metric instance space that admits a universally consistent rule -- the first
learning algorithm known to enjoy this property. However, its error and
compression rates have …

arxiv compression error lg on rules

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