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[2109.14412] Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification

ar5iv.labs.arxiv.org · 26,075 words · saved by 1 readers

We consider a variant of online binary classification where a learner sequentially assigns labels ( or ) to items with unknown true class. If, but only if, the learner chooses label they immediately observe the true l…

[2109.14412] Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification James A. Grant j.grant@lancaster.ac.uk; corresponding author Department of Mathematics and Statistics, Lancaster University, UK David S. Leslie d.leslie@lancaster.ac.uk Department of Mathematics and Statistics, Lancaster University, UK Abstract We consider a variant of online binary classification where a learner sequentially assigns labels ( 0 0 or 1 1 1 ) to items with unknown true class.

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