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» Missing Data Estimation Using Polynomial Kernels
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SIGMETRICS
2003
ACM
199views Hardware» more  SIGMETRICS 2003»
15 years 5 months ago
Data cache locking for higher program predictability
Caches have become increasingly important with the widening gap between main memory and processor speeds. However, they are a source of unpredictability due to their characteristi...
Xavier Vera, Björn Lisper, Jingling Xue
BMCBI
2008
186views more  BMCBI 2008»
15 years 18 days ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells
103
Voted
SPEECH
2010
136views more  SPEECH 2010»
14 years 11 months ago
Robust speech recognition by integrating speech separation and hypothesis testing
Missing data methods attempt to improve robust speech recognition by distinguishing between reliable and unreliable data in the time-frequency domain. Such methods require a binar...
Soundararajan Srinivasan, DeLiang L. Wang
111
Voted
BMCBI
2007
138views more  BMCBI 2007»
15 years 15 days ago
A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic
Background: A key challenge in metabonomics is to uncover quantitative associations between multidimensional spectroscopic data and biochemical measures used for disease risk asse...
Aki Vehtari, Ville-Petteri Mäkinen, Pasi Soin...
134
Voted
JAIR
2008
157views more  JAIR 2008»
15 years 14 days ago
Qualitative System Identification from Imperfect Data
Experience in the physical sciences suggests that the only realistic means of understanding complex systems is through the use of mathematical models. Typically, this has come to ...
George Macleod Coghill, Ashwin Srinivasan, Ross D....