Perplexity

Known as: Perplexity consumer, Perplexities, PP 
In information theory, perplexity is a measurement of how well a probability distribution or probability model predicts a sample. It may be used to… (More)
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Papers overview

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2014
2014
This paper studies the idea of removing low-frequency words from a corpus, which is a common practice to reduce computational… (More)
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Highly Cited
2012
Highly Cited
2012
We investigate the problem of domain adaptation for parallel data in Statistical Machine Translation (SMT). While techniques for… (More)
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Highly Cited
2012
Highly Cited
2012
Neural networks have become increasingly popular for the task of language modeling. Whereas feed-forward networks only exploit a… (More)
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Highly Cited
2010
Highly Cited
2010
A new recurrent neural network based language model (RNN LM) with applications to speech recognition is presented. Results… (More)
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2009
2009
An important task performed during the analysis of health news coverage is the identification of news articles that are related… (More)
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Highly Cited
2003
Highly Cited
2003
An empirical study has been conducted investigating the relationship between the performance of an aspect based language model in… (More)
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Highly Cited
2000
Highly Cited
2000
A goal of statistical language modeling is to learn the joint probability function of sequences of words in a language. This is… (More)
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Highly Cited
1999
Highly Cited
1999
Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent… (More)
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1997
1997
In this paper, we suggest a method to optimize the vocabulary for a given task using the perplexity criterion. The optimization… (More)
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Highly Cited
1995
Highly Cited
1995
Tn stochastic language modeling, backing-off is a widely used method to cope with the sparse data problem. In case of unseen… (More)
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