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Out-of-Distribution Detection using Maximum Entropy Coding
April 29, 2024, 4:42 a.m. | Mojtaba Abolfazli, Mohammad Zaeri Amirani, Anders H{\o}st-Madsen, June Zhang, Andras Bratincsak
cs.LG updates on arXiv.org arxiv.org
Abstract: Given a default distribution $P$ and a set of test data $x^M=\{x_1,x_2,\ldots,x_M\}$ this paper seeks to answer the question if it was likely that $x^M$ was generated by $P$. For discrete distributions, the definitive answer is in principle given by Kolmogorov-Martin-L\"{o}f randomness. In this paper we seek to generalize this to continuous distributions. We consider a set of statistics $T_1(x^M),T_2(x^M),\ldots$. To each statistic we associate its maximum entropy distribution and with this a universal source …
abstract arxiv coding cs.it cs.lg data detection distribution entropy generated math.it maximum paper question randomness seek set test type
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