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» Integrative missing value estimation for microarray data
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ICIP
2000
IEEE
14 years 8 months ago
Curve Evolution, Boundary-Value Stochastic Processes, the Mumford-Shah Problem, and Missing Data Applications
We present an estimation-theoretic approach to curve evolution for the Mumford-Shah problem. By viewing an active contour as the set of discontinuities in the Mumford-Shah problem...
Andy Tsai, Anthony J. Yezzi, Alan S. Willsky
BMCBI
2007
125views more  BMCBI 2007»
13 years 7 months ago
Bayesian meta-analysis models for microarray data: a comparative study
Background: With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis...
Erin M. Conlon, Joon J. Song, Anna Liu
DILS
2004
Springer
14 years 12 days ago
Heterogeneous Data Integration with the Consensus Clustering Formalism
Meaningfully integrating massive multi-experimental genomic data sets is becoming critical for the understanding of gene function. We have recently proposed methodologies for integ...
Vladimir Filkov, Steven Skiena
DASFAA
2007
IEEE
234views Database» more  DASFAA 2007»
14 years 1 months ago
Estimating Missing Data in Data Streams
Networks of thousands of sensors present a feasible and economic solution to some of our most challenging problems, such as real-time traffic modeling, military sensing and trackin...
Nan Jiang, Le Gruenwald
ICDM
2007
IEEE
145views Data Mining» more  ICDM 2007»
14 years 1 months ago
Using Data Mining to Estimate Missing Sensor Data
Estimating missing sensor values is an inherent problem in sensor network applications; however, existing data estimation approaches do not apply well to the context of datastream...
Le Gruenwald, Hamed Chok, Mazen Aboukhamis