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....
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 ...
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...
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...
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 ...