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Minimum Error Rate Training in Statistical Machine Translation
, 2003
"... Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training cri ..."
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Cited by 663 (7 self)
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Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training criteria which directly optimize translation quality.
A PostProcessing System To Yield Reduced Word Error Rates: Recognizer Output Voting Error Reduction (ROVER)
, 1997
"... This paper describes a system developed at NIST to produce a composite Automatic Speech Recognition (ASR) system output when the outputs of multiple ASR systems are available, and for which, in many cases, the composite ASR output has lower error rate than any of the individual systems. The system i ..."
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Cited by 406 (2 self)
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This paper describes a system developed at NIST to produce a composite Automatic Speech Recognition (ASR) system output when the outputs of multiple ASR systems are available, and for which, in many cases, the composite ASR output has lower error rate than any of the individual systems. The system
Modeling the effect of technology trends on the soft error rate of combinational logic
, 2002
"... This paper examines the effect of technology scaling and microarchitectural trends on the rate of soft errors in CMOS memory and logic circuits. We describe and validate an endtoend model that enables us to compute the soft error rates (SER) for existing and future microprocessorstyle designs. Th ..."
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Cited by 365 (8 self)
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This paper examines the effect of technology scaling and microarchitectural trends on the rate of soft errors in CMOS memory and logic circuits. We describe and validate an endtoend model that enables us to compute the soft error rates (SER) for existing and future microprocessorstyle designs
A direct approach to false discovery rates
, 2002
"... Summary. Multiplehypothesis testing involves guarding against much more complicated errors than singlehypothesis testing. Whereas we typically control the type I error rate for a singlehypothesis test, a compound error rate is controlled for multiplehypothesis tests. For example, controlling the ..."
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Cited by 749 (14 self)
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Summary. Multiplehypothesis testing involves guarding against much more complicated errors than singlehypothesis testing. Whereas we typically control the type I error rate for a singlehypothesis test, a compound error rate is controlled for multiplehypothesis tests. For example, controlling
Generalizations of the familywise error rate
 Ann. Statist
, 2005
"... Consider the problem of simultaneously testing null hypotheses H1,...,Hs. The usual approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. In many applications, particularly ..."
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Cited by 70 (7 self)
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Consider the problem of simultaneously testing null hypotheses H1,...,Hs. The usual approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. In many applications, particularly
Near Shannon limit errorcorrecting coding and decoding
, 1993
"... Abstract This paper deals with a new class of convolutional codes called Turbocodes, whose performances in terms of Bit Error Rate (BER) are close to the SHANNON limit. The TurboCode encoder is built using a parallel concatenation of two Recursive Systematic Convolutional codes and the associated ..."
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Cited by 1738 (5 self)
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Abstract This paper deals with a new class of convolutional codes called Turbocodes, whose performances in terms of Bit Error Rate (BER) are close to the SHANNON limit. The TurboCode encoder is built using a parallel concatenation of two Recursive Systematic Convolutional codes
AUC optimization vs. error rate minimization
 Advances in Neural Information Processing Systems
, 2004
"... The area under an ROC curve (AUC) is a criterion used in many applications to measure the quality of a classification algorithm. However, the objective function optimized in most of these algorithms is the error rate and not the AUC value. We give a detailed statistical analysis of the relationship ..."
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Cited by 148 (2 self)
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The area under an ROC curve (AUC) is a criterion used in many applications to measure the quality of a classification algorithm. However, the objective function optimized in most of these algorithms is the error rate and not the AUC value. We give a detailed statistical analysis of the relationship
Error and attack tolerance of complex networks
, 2000
"... Many complex systems display a surprising degree of tolerance against errors. For example, relatively simple organisms grow, persist and reproduce despite drastic pharmaceutical or environmental interventions, an error tolerance attributed to the robustness of the underlying metabolic network [1]. C ..."
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Cited by 974 (6 self)
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Many complex systems display a surprising degree of tolerance against errors. For example, relatively simple organisms grow, persist and reproduce despite drastic pharmaceutical or environmental interventions, an error tolerance attributed to the robustness of the underlying metabolic network [1
The control of the false discovery rate in multiple testing under dependency
 Annals of Statistics
, 2001
"... Benjamini and Hochberg suggest that the false discovery rate may be the appropriate error rate to control in many applied multiple testing problems. A simple procedure was given there as an FDR controlling procedure for independent test statistics and was shown to be much more powerful than comparab ..."
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Cited by 1058 (16 self)
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Benjamini and Hochberg suggest that the false discovery rate may be the appropriate error rate to control in many applied multiple testing problems. A simple procedure was given there as an FDR controlling procedure for independent test statistics and was shown to be much more powerful than
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