91 search results - page 3 / 19 » A nonparametric hierarchical bayesian framework for informat... |
AAAI
2010
13 years 7 months ago
2010
Matrix factorization is a fundamental technique in machine learning that is applicable to collaborative filtering, information retrieval and many other areas. In collaborative fil...
IPMI
2009
Springer
14 years 7 months ago
2009
Springer
In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model. Th...
RECOMB
2010
Springer
14 years 22 days ago
2010
Springer
Clustering methods are a useful and common first step in gene expression studies, but the results may be hard to interpret. We bring in explicitly an indicator of which genes tie ...
CORR
2010
Springer
13 years 4 months ago
2010
Springer
This paper proposes a nonparametric Bayesian method for exploratory data analysis and feature construction in continuous time series. Our method focuses on understanding shared fe...
JMLR
2010
13 years 1 months ago
2010
A non-parametric hierarchical Bayesian framework is developed for designing a classifier, based on a mixture of simple (linear) classifiers. Each simple classifier is termed a loc...