AI RESEARCH
Data Distribution Valuation Using Generalized Bayesian Inference
arXiv CS.LG
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ArXi:2604.05993v1 Announce Type: new We investigate the data distribution valuation problem, which aims to quantify the values of data distributions from their samples. This is a recently proposed problem that is related to but different from classical data valuation and can be applied to various applications. For this problem, we develop a novel framework called Generalized Bayes Valuation that utilizes generalized Bayesian inference with a loss constructed from transferability measures.