136 search results - page 9 / 28 » Bayesian Estimation of Kernel Bandwidth for Nonparametric Mo... |
SDM
2004
SIAM
14 years 11 months ago
2004
SIAM
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
NIPS
2008
14 years 11 months ago
2008
Kernel supervised learning methods can be unified by utilizing the tools from regularization theory. The duality between regularization and prior leads to interpreting regularizat...
MICCAI
2006
Springer
15 years 10 months ago
2006
Springer
Traditional techniques for statistical fMRI analysis are often based on thresholding of individual voxel values or averaging voxel values over a region of interest. In this paper w...
IJCAI
2007
14 years 11 months ago
2007
Nonparametric Bayesian mixture models, in particular Dirichlet process (DP) mixture models, have shown great promise for density estimation and data clustering. Given the size of ...
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CVPR
2010
IEEE
14 years 7 months ago
2010
IEEE
Pictorial structure (PS) models are extensively used for part-based recognition of scenes, people, animals and multi-part objects. To achieve tractability, the structure and param...