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#ml4science — Public Fediverse posts

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  1. This paper models "discovery" as being interested in finding things with high label values, have a big set of things to label, and can only label a few of the things once each. Similar to scientific discovery. The setting is more general than #bandits, and uses #ExperimentalDesign type ideas. The paper considers the ratio of expected instant regret to information gain as a rule for selecting the next item to label.
    arxiv.org/abs/2205.14829
    #MachineLearning #ml4science