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Dependent Hierarchical Beta Process for Image Interpolation and Denoising
Published on May 06, 20115506 Views
A dependent hierarchical beta process (dHBP) is developed as a prior for data that may be represented in terms of a sparse set of latent features, with covariate-dependent feature usage. The dHBP
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Chapter list
Dependent Hierarchical Beta Process for Image Interpolation and Denoising00:00
Outline00:16
Introduction: Background (1)00:45
Introduction: Background (2)01:29
Introduction: Motivation03:47
Introduction: Covariate Dependence05:27
Review of Beta Process06:43
Dependent Hierarchical Beta Process07:55
Dictionary Learning with dHBP10:34
Missing Data and Outliers12:40
MCMC Inference14:46
Experiments15:16
Image Interpolation: BP vs. dHBP (1)15:49
Image Interpolation: BP vs. dHBP (2)16:18
Image Interpolation: BP vs. dHBP (3)17:45
Image Interpolation: BP vs. dHBP (4)17:58
Image Interpolation: BP vs. dHBP (5)18:15
Image Interpolation: BP vs. dHBP (6)19:24
Future Work19:31
Conclusions20:21