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DART: Directed automated random testing
 In Programming Language Design and Implementation (PLDI
, 2005
"... We present a new tool, named DART, for automatically testing software that combines three main techniques: (1) automated extraction of the interface of a program with its external environment using static sourcecode parsing; (2) automatic generation of a test driver for this interface that performs ..."
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Cited by 843 (42 self)
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such as program crashes, assertion violations, and nontermination. Preliminary experiments to unit test several examples of C programs are very encouraging.
A Bayesian method for the induction of probabilistic networks from data
 MACHINE LEARNING
, 1992
"... This paper presents a Bayesian method for constructing probabilistic networks from databases. In particular, we focus on constructing Bayesian belief networks. Potential applications include computerassisted hypothesis testing, automated scientific discovery, and automated construction of probabili ..."
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Cited by 1400 (31 self)
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This paper presents a Bayesian method for constructing probabilistic networks from databases. In particular, we focus on constructing Bayesian belief networks. Potential applications include computerassisted hypothesis testing, automated scientific discovery, and automated construction
The effects of feedback interventions on performance: A historical review, a metaanalysis, and a preliminary feedback intervention theory
 Psychological Bulletin
, 1996
"... Since the beginning of the century, feedback interventions (FIs) produced negative—but largely ignored—effects on performance. A metaanalysis (607 effect sizes; 23,663 observations) suggests that FIs improved performance on average (d =.41) but that over '/3 of the FIs decreased performance. ..."
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Cited by 463 (1 self)
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mance. This finding cannot be explained by sampling error, feedback sign, or existing theories. The authors proposed a preliminary FI theory (FIT) and tested it with moderator analyses. The central assumption of FIT is that FIs change the locus of attention among 3 general and hierarchically organized levels
Estimating the Support of a HighDimensional Distribution
, 1999
"... Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We propo ..."
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Cited by 783 (29 self)
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Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We
ALLOCATION IN STRATIFIED SAMPLING BASED ON PRELIMINARY TESTS OF SIGNIFICANCE.
, 1971
"... Allocation in stratified sampling based on preliminary tests of significance ..."
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Allocation in stratified sampling based on preliminary tests of significance
Loopy belief propagation for approximate inference: An empirical study. In:
 Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" the use of Pearl's polytree algorithm in a Bayesian network with loops can perform well in the context of errorcorrecting codes. The most dramatic instance of this is the near Shannonlimit performanc ..."
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Cited by 676 (15 self)
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marginals at the last two iterations. We only plot the diseases which had nonnegligible posterior probability. Loopy Belief Propagation . s=o� . a' range of prior To test this hypothesis, we reparameterized the pyra mid network as follows: we set the prior probability of the "1"
Design and preliminary testing of an MRcompatible eye tracking system TAIMAZ BEGDJANI
"... Design and preliminary testing of an ..."
Preliminary Testing Procedures for Regression with Survey
"... We examine preliminary testing estimators for regression coefficients estimated with data from a complex survey. The ordinary least squares estimator is a common choice of researchers, but under an informative design, the ordinary least squares estimator is biased. The probability weighted estim ..."
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We examine preliminary testing estimators for regression coefficients estimated with data from a complex survey. The ordinary least squares estimator is a common choice of researchers, but under an informative design, the ordinary least squares estimator is biased. The probability weighted
ELDAS preliminary testvalidation
"... During the first ELDAS progress meeting we agreed upon the following course of action towards ..."
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During the first ELDAS progress meeting we agreed upon the following course of action towards
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