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On the Convergence Rate of GoodTuring Estimators
, 2000
"... GoodTuring adjustments of word frequencies are an important tool in natural language modeling. In particular, for any sample of words, there is a set of words not occuring in that sample. The total probability mass of the words not in the sample is the socalled missing mass. Good showed that the f ..."
Abstract

Cited by 44 (5 self)
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of the set of words occuring k times in the sample. 1 INTRODUCTION Since the publication of the GoodTuring estimators in 1953 [4], these estimators have been used extensively in language modeling applications [2, 3, 6]. In spite of the extensive use of GoodTuring estimators, little theoretical work has
On the Convergence Rate of GoodTuring Estimators
"... GoodTuring adjustments of word frequencies are an important tool in natural language modeling. In particular, for any sample of words, there is a set of words not occuring in that sample. The total probability mass of the words not in the sample is the socalled missing mass. Good showed that the f ..."
Abstract
 Add to MetaCart
GoodTuring adjustments of word frequencies are an important tool in natural language modeling. In particular, for any sample of words, there is a set of words not occuring in that sample. The total probability mass of the words not in the sample is the socalled missing mass. Good showed
On the Convergence Rate of GoodTuring Estimators
 In Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
, 2000
"... GoodTuring adjustments of word frequencies are an important tool in natural language modeling. In particular, for any sample of words, there is a set of words not occuring in that sample. The total probability mass of the words not in the sample is the socalled missing mass. Good showed that the f ..."
Abstract
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of the set of words occuring k times in the sample. 1 Introduction Since the publication of the GoodTuring estimators in 1953 [4], these estimators have been used extensively in language modeling applications [2, 5, 3]. In spite of the extensive use of GoodTuring estimators, little theoretical work has
Optimization Flow Control, I: Basic Algorithm and Convergence
 IEEE/ACM TRANSACTIONS ON NETWORKING
, 1999
"... We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using gradient projection algorithm. In thi ..."
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Cited by 690 (64 self)
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We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using gradient projection algorithm
Social change and crime rate trends: a routine activity approach
 American Sociological Review
, 1979
"... In this paper we present a "routine activity approach " for analyzing crime rate trends and cycles. Rather than emphasizing the characteristics of offenders, with this approach we concentrate upon the circumstances in which they carry out predatory criminal acts. Most criminal acts require ..."
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Cited by 657 (5 self)
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In this paper we present a "routine activity approach " for analyzing crime rate trends and cycles. Rather than emphasizing the characteristics of offenders, with this approach we concentrate upon the circumstances in which they carry out predatory criminal acts. Most criminal acts
Reopening the Convergence Debate: A new look at crosscountry growth empirics
 JOURNAL OF ECONOMIC GROWTH
, 1996
"... ..."
Maximum Likelihood Phylogenetic Estimation from DNA Sequences with Variable Rates over Sites: Approximate Methods
 J. Mol. Evol
, 1994
"... Two approximate methods are proposed for maximum likelihood phylogenetic estimation, which allow variable rates of substitution across nucleotide sites. Three data sets with quite different characteristics were analyzed to examine empirically the performance of these methods. The first, called ..."
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Cited by 540 (28 self)
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Two approximate methods are proposed for maximum likelihood phylogenetic estimation, which allow variable rates of substitution across nucleotide sites. Three data sets with quite different characteristics were analyzed to examine empirically the performance of these methods. The first, called
Estimation and Inference in Econometrics
, 1993
"... The astonishing increase in computer performance over the past two decades has made it possible for economists to base many statistical inferences on simulated, or bootstrap, distributions rather than on distributions obtained from asymptotic theory. In this paper, I review some of the basic ideas o ..."
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Cited by 1151 (3 self)
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The astonishing increase in computer performance over the past two decades has made it possible for economists to base many statistical inferences on simulated, or bootstrap, distributions rather than on distributions obtained from asymptotic theory. In this paper, I review some of the basic ideas of bootstrap inference. The paper discusses Monte Carlo tests, several types of bootstrap test, and bootstrap confidence intervals. Although bootstrapping often works well, it does not do so in every case.
Estimating Wealth Effects without Expenditure Data— or Tears
 Policy Research Working Paper 1980, The World
, 1998
"... Abstract: We use the National Family Health Survey (NFHS) data collected in Indian states in 1992 and 1993 to estimate the relationship between household wealth and the probability a child (aged 6 to 14) is enrolled in school. A methodological difficulty to overcome is that the NFHS, modeled closely ..."
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Cited by 832 (16 self)
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Abstract: We use the National Family Health Survey (NFHS) data collected in Indian states in 1992 and 1993 to estimate the relationship between household wealth and the probability a child (aged 6 to 14) is enrolled in school. A methodological difficulty to overcome is that the NFHS, modeled
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.
Results 1  10
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