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- W2105558440 abstract "Bayesian hypothesis testing is investigated when the prior probabilities of the hypotheses, taken as a random vector, must be quantized. Nearest neighbor and centroid conditions for quantizer optimality are derived using mean Bayes risk error as a distortion measure. An example of optimal quantization for hypothesis testing is provided. Human decision making is briefly studied assuming quantized prior Bayesian hypothesis testing; this model explains several experimental findings." @default.
- W2105558440 created "2016-06-24" @default.
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- W2105558440 date "2008-03-01" @default.
- W2105558440 modified "2023-09-25" @default.
- W2105558440 title "Minimum mean bayes risk error quantization of prior probabilities" @default.
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- W2105558440 doi "https://doi.org/10.1109/icassp.2008.4518392" @default.
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