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JMLR
2012
11 years 7 months ago
Hierarchical Latent Dictionaries for Models of Brain Activation
In this work, we propose a hierarchical latent dictionary approach to estimate the timevarying mean and covariance of a process for which we have only limited noisy samples. We fu...
Alona Fyshe, Emily B. Fox, David B. Dunson, Tom M....
LREC
2010
141views Education» more  LREC 2010»
13 years 6 months ago
Evaluating Semantic Relations and Distances in the Associative Concept Dictionary using NIRS-imaging
In this study, we extracted brain activities related to semantic relations and distances to improve the precision of distance calculation among concepts in the Associated Concept ...
Nao Tatsumi, Jun Okamoto, Shun Ishizaki
NIPS
2008
13 years 5 months ago
Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images
We propose a novel hierarchical, nonlinear model that predicts brain activity in area V1 evoked by natural images. In the study reported here brain activity was measured by means ...
Pradeep Ravikumar, Vincent Q. Vu, Bin Yu, Thomas N...
ICASSP
2011
IEEE
12 years 8 months ago
Covariate-dependent dictionary learning and sparse coding
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 (dictionary elements), with covar...
Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, Dav...
ICML
2009
IEEE
14 years 5 months ago
Unsupervised hierarchical modeling of locomotion styles
This paper describes an unsupervised learning technique for modeling human locomotion styles, such as distinct related activities (e.g. running and striding) or variations of the ...
Wei Pan, Lorenzo Torresani