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» Measuring independence of datasets
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BMCBI
2006
153views more  BMCBI 2006»
13 years 11 months ago
Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments
Background: The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating v...
Maureen A. Sartor, Craig R. Tomlinson, Scott C. We...
ICPR
2000
IEEE
14 years 12 months ago
General Bias/Variance Decomposition with Target Independent Variance of Error Functions Derived from the Exponential Family of D
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
Jakob Vogdrup Hansen, Tom Heskes
CCR
2008
109views more  CCR 2008»
13 years 11 months ago
An independent H-TCP implementation under FreeBSD 7.0: description and observed behaviour
A key requirement for IETF recognition of new TCP algorithms is having an independent, interoperable implementation. This paper describes our BSD-licensed implementation of H-TCP ...
Grenville J. Armitage, Lawrence Stewart, Michael W...
IISWC
2006
IEEE
14 years 4 months ago
Comparing Benchmarks Using Key Microarchitecture-Independent Characteristics
— Understanding the behavior of emerging workloads is important for designing next generation microprocessors. For addressing this issue, computer architects and performance anal...
Kenneth Hoste, Lieven Eeckhout
IJAR
2010
91views more  IJAR 2010»
13 years 9 months ago
Logical and algorithmic properties of stable conditional independence
The logical and algorithmic properties of stable conditional independence (CI) as an alternative structural representation of conditional independence information are investigated...
Mathias Niepert, Dirk Van Gucht, Marc Gyssens