Results 1 to 10 of about 104,862 (79)
Hierarchical Bayesian sparse image reconstruction with application to MRFM [PDF]
, 2008 This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gaussian noise. Our hierarchical Bayes model is well suited to such naturally
Dobigeon, Nicolas +2 more
core +8 more sources
Asymptotic Accuracy of Bayesian Estimation for a Single Latent Variable [PDF]
, 2015 In data science and machine learning, hierarchical parametric models, such as mixture models, are often used. They contain two kinds of variables: observable variables, which represent the parts of the data that can be directly measured, and latent ...
Yamazaki, Keisuke
core +1 more source
Generation of folk song melodies using Bayes transforms [PDF]
, 2011 The paper introduces the `Bayes transform', a mathematical procedure for putting data into a hierarchical representation. Applicable to any type of data, the procedure yields interesting results when applied to sequences. In this case, the representation
Bent I. +27 more
core +1 more source
A nonparametric empirical Bayes framework for large-scale multiple testing [PDF]
, 2011 We propose a flexible and identifiable version of the two-groups model, motivated by hierarchical Bayes considerations, that features an empirical null and a semiparametric mixture model for the non-null cases.
Choe +7 more
core +1 more source
Hierarchic Bayesian models for kernel learning [PDF]
, 2005 The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance when compared to that obtained from any single data source.
Girolami, M., Rogers, S.
core +2 more sources
, 2010 This paper considers estimation of the predictive density for a normal linear model with unknown variance under alpha-divergence loss for -1
Maruyama, Yuzo, Strawderman, William E.
core +1 more source
Nonparametric Bayes modeling of count processes [PDF]
, 2013 Data on count processes arise in a variety of applications, including longitudinal, spatial and imaging studies measuring count responses. The literature on statistical models for dependent count data is dominated by models built from hierarchical ...
Canale, Antonio, Dunson, David B.
core +2 more sources
Empirical Bayes and Hierarchical Bayes Estimation of Skew Normal Populations [PDF]
, 2008 We develop empirical and hierarchical Bayesian methodologies for the skew normal populations through the EM algorithm and the Gibbs sampler. A general concept of skewness to the normal distribution is considered throughout.
Bansal, Naveen K. +2 more
core +1 more source
A New Hierarchical Redundancy Eliminated Tree Augmented Naive Bayes Classifier for Coping with Gene Ontology-based Features [PDF]
, 2016 The Tree Augmented Naive Bayes classifier is a type of probabilistic graphical model that can represent some feature dependencies. In this work, we propose a Hierarchical Redundancy Eliminated Tree Augmented Naive Bayes (HRE-TAN) algorithm, which ...
Freitas, Alex A., Wan, Cen
core +2 more sources
A Hierarchical Bayes Ensemble Kalman Filter
, 2016 A new ensemble filter that allows for the uncertainty in the prior distribution is proposed and tested. The filter relies on the conditional Gaussian distribution of the state given the model-error and predictability-error covariance matrices. The latter
Rakitko, Alexander, Tsyrulnikov, Michael
core +1 more source