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» Embedding Heterogeneous Data Using Statistical Models
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141
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ICASSP
2009
IEEE
15 years 9 months ago
Microarray classification using block diagonal linear discriminant analysis with embedded feature selection
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
Lingyan Sheng, Roger Pique-Regi, Shahab Asgharzade...
123
Voted
ICML
2008
IEEE
16 years 3 months ago
Statistical models for partial membership
We present a principled Bayesian framework for modeling partial memberships of data points to clusters. Unlike a standard mixture model which assumes that each data point belongs ...
Katherine A. Heller, Sinead Williamson, Zoubin Gha...
MASCOTS
2010
15 years 3 months ago
Examining Energy Use in Heterogeneous Archival Storage Systems
Controlling energy usage in data centers, and storage in particular, continues to rise in importance. Many systems and models have examined energy efficiency through intelligent sp...
Ian F. Adams, Ethan L. Miller, Mark W. Storer
142
Voted
EMSOFT
2009
Springer
15 years 8 months ago
Analytic real-time analysis and timed automata: a hybrid method for analyzing embedded real-time systems
This paper advocates a strict compositional and hybrid approach for obtaining key (performance) metrics of embedded At its core the developed methodology abstracts system componen...
Kai Lampka, Simon Perathoner, Lothar Thiele
BMCBI
2010
97views more  BMCBI 2010»
15 years 2 months ago
Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on es...
Dirk Repsilber, Sabine Kern, Anna Telaar, Gerhard ...