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» A Hierarchical Latent Variable Model for Data Visualization
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BMCBI
2008
118views more  BMCBI 2008»
13 years 9 months ago
Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling
Background: With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few appro...
Grace S. Shieh, Chung-Ming Chen, Ching-Yun Yu, Jui...
NIPS
2004
13 years 10 months ago
Parametric Embedding for Class Visualization
In this paper, we propose a new method, Parametric Embedding (PE), for visualizing the posteriors estimated over a mixture model. PE simultaneously embeds both objects and their c...
Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean S...
ICIP
2008
IEEE
14 years 3 months ago
Total variation super resolution using a variational approach
In this paper we propose a novel algorithm for super resolution based on total variation prior and variational distribution approximations. We formulate the problem using a hierar...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
ACML
2009
Springer
14 years 3 months ago
Linear Time Model Selection for Mixture of Heterogeneous Components
Abstract: Our main contribution is to propose a novel model selection methodology, expectation minimization of information criterion (EMIC). EMIC makes a significant impact on the...
Ryohei Fujimaki, Satoshi Morinaga, Michinari Momma...
EDBT
2006
ACM
266views Database» more  EDBT 2006»
14 years 9 months ago
From Analysis to Interactive Exploration: Building Visual Hierarchies from OLAP Cubes
We present a novel framework for comprehensive exploration of OLAP data by means of user-defined dynamic hierarchical visualizations. The multidimensional data model behind the OLA...
Svetlana Vinnik, Florian Mansmann