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EMMCVPR
2005
Springer
15 years 9 months ago
Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...
Sanjiv Kumar, Jonas August, Martial Hebert
IJCNLP
2005
Springer
15 years 9 months ago
Using Multiple Discriminant Analysis Approach for Linear Text Segmentation
Research on linear text segmentation has been an on-going focus in NLP for the last decade, and it has great potential for a wide range of applications such as document summarizati...
Jingbo Zhu, Na Ye, Xinzhi Chang, Wenliang Chen, Be...
CSB
2005
IEEE
165views Bioinformatics» more  CSB 2005»
15 years 6 months ago
Sequential Diagonal Linear Discriminant Analysis (SeqDLDA) for Microarray Classification and Gene Identification
In microarray classification we are faced with a very large number of features and very few training samples. This is a challenge for classical Linear Discriminant Analysis (LDA),...
Roger Pique-Regi, Antonio Ortega, Shahab Asgharzad...
ACL
2006
15 years 5 months ago
Discriminative Word Alignment with Conditional Random Fields
In this paper we present a novel approach for inducing word alignments from sentence aligned data. We use a Conditional Random Field (CRF), a discriminative model, which is estima...
Phil Blunsom, Trevor Cohn
NIPS
2008
15 years 5 months ago
Generative and Discriminative Learning with Unknown Labeling Bias
We apply robust Bayesian decision theory to improve both generative and discriminative learners under bias in class proportions in labeled training data, when the true class propo...
Miroslav Dudík, Steven J. Phillips