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» Extractive summarization using a latent variable model
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UAI
2004
14 years 11 months ago
Convolutional Factor Graphs as Probabilistic Models
Based on a recent development in the area of error control coding, we introduce the notion of convolutional factor graphs (CFGs) as a new class of probabilistic graphical models. ...
Yongyi Mao, Frank R. Kschischang, Brendan J. Frey
75
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ICPR
2000
IEEE
15 years 1 months ago
Constrained Mixture Modeling of Intrinsically Low-Dimensional Distributions
In this paper we introduce a novel way of modeling distributions with a low latent dimensionality. Our method allows for a strict control of the properties of the mapping between ...
Joris Portegies Zwart, Ben J. A. Kröse
SIGIR
2002
ACM
14 years 9 months ago
Generic summarization and keyphrase extraction using mutual reinforcement principle and sentence clustering
A novel method for simultaneous keyphrase extraction and generic text summarization is proposed by modeling text documents as weighted undirected and weighted bipartite graphs. Sp...
Hongyuan Zha
ICCV
2007
IEEE
15 years 3 months ago
Latent Model Clustering and Applications to Visual Recognition
We consider clustering situations in which the pairwise affinity between data points depends on a latent ”context” variable. For example, when clustering features arising fro...
Simon Polak, Amnon Shashua
IDA
2005
Springer
15 years 3 months ago
Probabilistic Latent Clustering of Device Usage
Abstract. We investigate an application of Probabilistic Latent Semantics to the problem of device usage analysis in an infrastructure in which multiple users have access to a shar...
Jean-Marc Andreoli, Guillaume Bouchard