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» Extractive summarization using a latent variable model
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CVPR
2010
IEEE
13 years 8 months ago
Modeling pixel means and covariances using factorized third-order boltzmann machines
Learning a generative model of natural images is a useful way of extracting features that capture interesting regularities. Previous work on learning such models has focused on me...
Marc Aurelio Ranzato, Geoffrey E. Hinton
ACL
2000
13 years 9 months ago
Headline Generation Based on Statistical Translation
Extractive summarization techniques cannot generate document summaries shorter than a single sentence, something that is often required. An ideal summarization system would unders...
Michele Banko, Vibhu O. Mittal, Michael J. Witbroc...
CONTEXT
2007
Springer
14 years 1 months ago
Thai Text Coherence Structuring with Coordinating and Subordinating Relations for Text Summarization
Text summarization with the consideration of coherence can be achieved by using discourse processing with the Rhetorical Structure Theory (RST). Additional problems on relational a...
Thana Sukvaree, Asanee Kawtrakul, Jean Caelen
BMCBI
2007
138views more  BMCBI 2007»
13 years 7 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...
ICASSP
2011
IEEE
12 years 11 months ago
A partial least squares framework for speaker recognition
Modern approaches to speaker recognition (verification) operate in a space of “supervectors” created via concatenation of the mean vectors of a Gaussian mixture model (GMM) a...
Balaji Vasan Srinivasan, Dmitry N. Zotkin, Ramani ...