RESEARCHarXiv CS.LG·5d ago
Bayes-Sufficient Representations in Supervised Learning
This work defines Bayes-sufficient representations for supervised learning, focusing on information relevant for prediction based on a fixed decision problem and loss function. It introduces the concept of a Bayes quotient and connects the framework to property elicitation, showing how different loss functions require specific Bayes-optimal actions.
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