Results 231 to 240 of about 50,616 (261)
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AUC Maximization in Bayesian Hierarchical Models
2016The area under the curve (AUC) measures such as the area under the receiver operating characteristics curve (AUROC) and the area under the precision-recall curve (AUPR) are known to be more appropriate than the error rate, especially, for imbalanced data sets.
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Bayesian Hierarchical Pointing Models
Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology, 2022Hang Zhao 0005 +3 more
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Learning overhypotheses with hierarchical Bayesian models
Developmental Science, 2007AbstractInductive learning is impossible without overhypotheses, or constraints on the hypotheses considered by the learner. Some of these overhypotheses must be innate, but we suggest that hierarchical Bayesian models can help to explain how the rest are acquired.
Kemp, C., Perfors, A., Tenenbaum, J.
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Hierarchical Bayesian models of cognitive development
Biological Cybernetics, 2016This article provides an introductory overview of the state of research on Hierarchical Bayesian Modeling in cognitive development. First, a brief historical summary and a definition of hierarchies in Bayesian modeling are given. Subsequently, some model structures are described based on four examples in the literature.
Thomas Glassen, Verena Nitsch
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A hierarchical Bayesian model for pattern recognition
The 2012 International Joint Conference on Neural Networks (IJCNN), 2012The success of automated classification hinges on the choice of the representation of the data. Much research has focused on feature extraction techniques that can identify highly informative representations of a dataset. In this paper, we adapt for the purposes of classification a hierarchical Bayesian model developed by Karklin and Lewicki to model ...
Ashwini Shikaripur Nadig, Brian Potetz
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Bayesian Hierarchical Models for Subgroup Analysis
Pharmaceutical StatisticsABSTRACTIn conventional subgroup analyses, subgroup treatment effects are estimated using data from each subgroup separately without considering data from other subgroups in the same study. The subgroup treatment effects estimated this way may be heterogenous with high variability due to small sample sizes in some subgroups and much different from the ...
Yun Wang +9 more
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Bayesian hierarchical models for the prediction of volleyball results
Journal of Applied Statistics, 2021Andrea Gabrio
exaly
Bayesian Network Structure Inference with an Hierarchical Bayesian Model
2010Bayesian Networks (BNs) are applied to a wide range of applications. In the past few years great interest is dedicated to the problem of inferring the structure of BNs solely from the data. In this work we explore a probabilistic method which enables the inclusion of extra knowledge in the inference of BNs.
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Bayesian hierarchical models for linear networks
Journal of Applied Statistics, 2022Yinghui Wei, Rana Moyeed
exaly