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ICML
1999
IEEE
16 years 13 days ago
1999
IEEE
Lbr is a lazy semi-naive Bayesian classi er learning technique, designed to alleviate the attribute interdependence problem of naive Bayesian classi cation. To classify a test exa...
TACAS
2007
Springer
15 years 5 months ago
2007
Springer
Symbolic execution can be problematic when applied to real applications. This paper addresses two of these problems: (1) the constraints generated during symbolic execution may be ...
CSDA
2006
14 years 11 months ago
2006
We explore different approaches for performing hypothesis tests on the shape of a mean function by developing general methodologies both, for the often assumed, i.i.d. error struc...
CAV
2005
Springer
15 years 5 months ago
2005
Springer
Abstract. In predicate abstraction, exact image computation is problematic, requiring in the worst case an exponential number of calls to a decision procedure. For this reason, sof...
BMCBI
2008
14 years 11 months ago
2008
Background: False discovery rate (FDR) methods play an important role in analyzing highdimensional data. There are two types of FDR, tail area-based FDR and local FDR, as well as ...