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ICML
1999
IEEE
14 years 8 months ago
Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees
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...
Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting
TACAS
2007
Springer
125views Algorithms» more  TACAS 2007»
14 years 1 months ago
Type-Dependence Analysis and Program Transformation for Symbolic Execution
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 ...
Saswat Anand, Alessandro Orso, Mary Jean Harrold
CSDA
2006
84views more  CSDA 2006»
13 years 7 months ago
Performing hypothesis tests on the shape of functional data
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...
Gareth M. James, Ashish Sood
CAV
2005
Springer
122views Hardware» more  CAV 2005»
14 years 1 months ago
Interpolant-Based Transition Relation Approximation
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...
Ranjit Jhala, Kenneth L. McMillan
BMCBI
2008
129views more  BMCBI 2008»
13 years 7 months ago
A unified approach to false discovery rate estimation
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 ...
Korbinian Strimmer