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» Learning the Structure of Linear Latent Variable Models
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JMLR
2012
11 years 11 months ago
A Bayesian Analysis of the Radioactive Releases of Fukushima
The Fukushima Daiichi disaster 11 March, 2011 is considered the largest nuclear accident since the 1986 Chernobyl disaster and has been rated at level 7 on the International Nucle...
Ryota Tomioka, Morten Mørup
CVPR
2006
IEEE
14 years 11 months ago
Using Dependent Regions for Object Categorization in a Generative Framework
"Bag of words" models have enjoyed much attention and achieved good performances in recent studies of object categorization. In most of these works, local patches are mo...
Gang Wang, Ye Zhang, Fei-Fei Li 0002
PAMI
2006
136views more  PAMI 2006»
13 years 8 months ago
Data Driven Image Models through Continuous Joint Alignment
This paper presents a family of techniques that we call congealing for modeling image classes from data. The idea is to start with a set of images and make them appear as similar a...
Erik G. Learned-Miller
ICASSP
2011
IEEE
13 years 17 days ago
A hierarchical generative model for Generic Audio Document Categorization
In this paper, we call the pattern classification problem that consists in assigning a category label to a long audio signal based on its semantic content as Generic Audio Documen...
Zhi Zeng, Shuwu Zhang
CORR
2010
Springer
70views Education» more  CORR 2010»
13 years 9 months ago
Structured sparsity-inducing norms through submodular functions
Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
Francis Bach