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NECO
2002
104views more  NECO 2002»
13 years 8 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen
KBSE
2007
IEEE
14 years 3 months ago
An automated approach to monitoring and diagnosing requirements
Monitoring the satisfaction of software requirements and diagnosing what went wrong in case of failure is a hard problem that has received little attention in the Software and Req...
Yiqiao Wang, Sheila A. McIlraith, Yijun Yu, John M...
BMCBI
2005
163views more  BMCBI 2005»
13 years 9 months ago
Rank-invariant resampling based estimation of false discovery rate for analysis of small sample microarray data
Background: The evaluation of statistical significance has become a critical process in identifying differentially expressed genes in microarray studies. Classical p-value adjustm...
Nitin Jain, HyungJun Cho, Michael O'Connell, Jae K...
ICIP
2004
IEEE
14 years 10 months ago
Multisensor raster and vector data fusion based on uncertainty modeling
We propose a new methodology for fusing temporally changing multisensor raster and vector data by developing a spatially and temporally varying uncertainty model of acquired and t...
Sang-Chul Lee, Peter Bajcsy
DILS
2004
Springer
14 years 24 days ago
An Ontology-Driven Framework for Data Transformation in Scientific Workflows
Abstract. Ecologists spend considerable effort integrating heterogeneous data for statistical analyses and simulations, for example, to run and test predictive models. Our research...
Shawn Bowers, Bertram Ludäscher