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Conditional random field
Known as:
CRF
, Conditional random fields
, Discriminative probabilistic latent variable model
Conditional random fields (CRFs) are a class of statistical modelling method often applied in pattern recognition and machine learning, where they…
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Related topics
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46 relations
.NET Framework
Activity recognition
Bioinformatics
C++
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Broader (1)
Machine learning
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2015
2015
Prostate Cancer Detection via a Quantitative Radiomics-Driven Conditional Random Field Framework
A. Chung
,
F. Khalvati
,
M. Shafiee
,
M. Haider
,
A. Wong
IEEE Access
2015
Corpus ID: 6430568
The use of high-volume quantitative radiomics features extracted from multi-parametric magnetic resonance imaging (MP-MRI) is…
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Review
2014
Review
2014
Hierarchical Multi-label Conditional Random Fields for Aspect-Oriented Opinion Mining
Diego Marcheggiani
,
Oscar Täckström
,
Andrea Esuli
,
F. Sebastiani
European Conference on Information Retrieval
2014
Corpus ID: 6864299
A common feature of many online review sites is the use of an overall rating that summarizes the opinions expressed in a review…
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Highly Cited
2010
Highly Cited
2010
Learning Tree Conditional Random Fields
Joseph K. Bradley
,
Carlos Guestrin
International Conference on Machine Learning
2010
Corpus ID: 14203763
We examine maximum spanning tree-based methods for learning the structure of tree Conditional Random Fields (CRFs) P(Y|Χ). We use…
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Highly Cited
2009
Highly Cited
2009
Hidden Conditional Random Fields for phone recognition
Yun-Hsuan Sung
,
Dan Jurafsky
IEEE Workshop on Automatic Speech Recognition…
2009
Corpus ID: 6355586
We apply Hidden Conditional Random Fields (HCRFs) to the task of TIMIT phone recognition. HCRFs are discriminatively trained…
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Highly Cited
2007
Highly Cited
2007
Document Summarization Using Conditional Random Fields
Dou Shen
,
Jian-Tao Sun
,
Hua Li
,
Qiang Yang
,
Zheng Chen
International Joint Conference on Artificial…
2007
Corpus ID: 126818
Many methods, including supervised and unsupervised algorithms, have been developed for extractive document summarization. Most…
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Highly Cited
2006
Highly Cited
2006
Accelerated training of conditional random fields with stochastic gradient methods
S. V. N. Vishwanathan
,
N. Schraudolph
,
Mark W. Schmidt
,
Kevin P. Murphy
International Conference on Machine Learning
2006
Corpus ID: 1978101
We apply Stochastic Meta-Descent (SMD), a stochastic gradient optimization method with gain vector adaptation, to the training of…
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Highly Cited
2006
Highly Cited
2006
Combining phonetic attributes using conditional random fields
Jeremy Morris
,
E. Fosler-Lussier
Interspeech
2006
Corpus ID: 11305607
A Conditional Random Field is a mathematical model for sequences that is similar in many ways to a Hidden Markov Model, but is…
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Highly Cited
2006
Highly Cited
2006
Hidden-state Conditional Random Fields
A. Quattoni
,
S. Wang
,
Louis-Philippe Morency
,
M. Collins
,
Trevor Darrell
2006
Corpus ID: 13645707
We present a discriminative latent variable model for classification problems in structured domains where inputs can be…
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Highly Cited
2003
Highly Cited
2003
Tax Compliance as a Coordination Game
J. Alm
,
M. McKee
2003
Corpus ID: 54188536
This paper uses laboratory experiments to investigate compliance behavior when returns are selected for audit based upon the…
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Highly Cited
1975
Highly Cited
1975
Release of imnumoreactive luteinising hormone-releasing hormone and thyrotrophin-releasing hormone from hypothalamic synaptosomes
G. W. Bennett
,
J. Edwardson
,
D. Holland
,
S. Jeffcoate
,
N. White
Nature
1975
Corpus ID: 4164905
THE hypophysiotropic hypothalamus regulates the secretion of the anterior pituitary gland through the production and release of…
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