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4,275
On the optimality of the simple Bayesian classifier under zeroone loss
 MACHINE LEARNING
, 1997
"... The simple Bayesian classifier is known to be optimal when attributes are independent given the class, but the question of whether other sufficient conditions for its optimality exist has so far not been explored. Empirical results showing that it performs surprisingly well in many domains containin ..."
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Cited by 818 (27 self)
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The simple Bayesian classifier is known to be optimal when attributes are independent given the class, but the question of whether other sufficient conditions for its optimality exist has so far not been explored. Empirical results showing that it performs surprisingly well in many domains
Maximum Likelihood Linear Transformations for HMMBased Speech Recognition
 COMPUTER SPEECH AND LANGUAGE
, 1998
"... This paper examines the application of linear transformations for speaker and environmental adaptation in an HMMbased speech recognition system. In particular, transformations that are trained in a maximum likelihood sense on adaptation data are investigated. Other than in the form of a simple bias ..."
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Cited by 570 (68 self)
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This paper examines the application of linear transformations for speaker and environmental adaptation in an HMMbased speech recognition system. In particular, transformations that are trained in a maximum likelihood sense on adaptation data are investigated. Other than in the form of a simple
Segmentation of brain MR images through a hidden Markov random field model and the expectationmaximization algorithm
 IEEE TRANSACTIONS ON MEDICAL. IMAGING
, 2001
"... The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogrambased model, the FM has an intrinsic limi ..."
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Cited by 639 (15 self)
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The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogrambased model, the FM has an intrinsic
Semantics of ContextFree Languages
 In Mathematical Systems Theory
, 1968
"... "Meaning " may be assigned to a string in a contextfree language by defining "attributes " of the symbols in a derivation tree for that string. The attributes can be defined by functions associated with each production in the grammar. This paper examines the implications of th ..."
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Cited by 569 (0 self)
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. An algorithm is given which detects when such semantic rules could possibly lead to circular definition of some attributes. An example is given of a simple programming language defined with both inherited and synthesized attributes, and the method of definition is compared to other techniques for formal
A Simple Biased Distribution for Dinur’s Construction
, 2006
"... The Dinur construction [Din05] achieves gap amplification, by repeatedly applying first a powering construction – which increases the gap, but also increases the alphabet size – and then applying a construction to reduce the alphabet size (which diminishes the gap but not by too much). The latter c ..."
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The Dinur construction [Din05] achieves gap amplification, by repeatedly applying first a powering construction – which increases the gap, but also increases the alphabet size – and then applying a construction to reduce the alphabet size (which diminishes the gap but not by too much). The latter construction is based on long codes and is not the focus of the current paper.
Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score
, 2000
"... We are interested in estimating the average effect of a binary treatment on a scalar outcome. If assignment to the treatment is independent of the potential outcomes given pretreatment variables, biases associated with simple treatmentcontrol average comparisons can be removed by adjusting for diff ..."
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Cited by 416 (35 self)
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We are interested in estimating the average effect of a binary treatment on a scalar outcome. If assignment to the treatment is independent of the potential outcomes given pretreatment variables, biases associated with simple treatmentcontrol average comparisons can be removed by adjusting
Forecasting bankruptcy more accurately: a simple hazard model
 0 otherwise P (Yit = 1) = FLOGIT (z 0 (i;t) ) with Yit = 1 , Y it < 0 where Y it = c + Z 0 (i;t) + " (i;t) and the
, 2001
"... I argue that hazard models are more appropriate for forecasting bankruptcy than the singleperiod models used previously. Singleperiod bankruptcy models give biased and inconsistent probability estimates while hazard models produce consistent estimates. I describe a simple technique for estimating ..."
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Cited by 358 (1 self)
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I argue that hazard models are more appropriate for forecasting bankruptcy than the singleperiod models used previously. Singleperiod bankruptcy models give biased and inconsistent probability estimates while hazard models produce consistent estimates. I describe a simple technique for estimating
A simple bias correction algorithm for use in data assimilation
 Goddard Space Flight Center, Greenbelt, MD
, 1996
"... This paper has not been published and should be regarded as an Internal Report from DAO. Permission to quote from it should be obtained from the DAO. ..."
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Cited by 1 (0 self)
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This paper has not been published and should be regarded as an Internal Report from DAO. Permission to quote from it should be obtained from the DAO.
and fill: a simple funnelplotbased method of testing and adjusting for publication bias in metaanalysis. Biometrics 2000;56:455–63
"... SUMMARY. We study recently developed nonparametric methods for estimating the number of missing studies that might exist in a metaanalysis and the effect that these studies might have had on its outcome. These are simple rankbased data augmentation techniques, which formalize the use of funnel plo ..."
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Cited by 312 (1 self)
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SUMMARY. We study recently developed nonparametric methods for estimating the number of missing studies that might exist in a metaanalysis and the effect that these studies might have had on its outcome. These are simple rankbased data augmentation techniques, which formalize the use of funnel
The twoparameter PoissonDirichlet distribution derived from a stable subordinator.
, 1995
"... The twoparameter PoissonDirichlet distribution, denoted pd(ff; `), is a distribution on the set of decreasing positive sequences with sum 1. The usual PoissonDirichlet distribution with a single parameter `, introduced by Kingman, is pd(0; `). Known properties of pd(0; `), including the Markov ..."
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Cited by 356 (33 self)
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chain description due to VershikShmidtIgnatov, are generalized to the twoparameter case. The sizebiased random permutation of pd(ff; `) is a simple residual allocation model proposed by Engen in the context of species diversity, and rediscovered by Perman and the authors in the study of excursions
Results 1  10
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4,275