Feb. 12, 2024, 5:43 a.m. | Vinod Raman Unique Subedi Ananth Raman Ambuj Tewari

cs.LG updates on arXiv.org arxiv.org

In online binary classification under \emph{apple tasting} feedback, the learner only observes the true label if it predicts ``1". First studied by \cite{helmbold2000apple}, we revisit this classical partial-feedback setting and study online learnability from a combinatorial perspective. We show that the Littlestone dimension continues to provide a tight quantitative characterization of apple tasting in the agnostic setting, closing an open question posed by \cite{helmbold2000apple}. In addition, we give a new combinatorial parameter, called the Effective width, that tightly quantifies the …

apple binary classification cs.lg dimensions feedback minimax perspective quantitative show stat.ml study tasting true

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