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» Models for Representing Task Ontologies
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IJCAI
2003
13 years 11 months ago
Hierarchical Hidden Markov Models for Information Extraction
Information extraction can be defined as the task of automatically extracting instances of specified classes or relations from text. We consider the case of using machine learni...
Marios Skounakis, Mark Craven, Soumya Ray
JMLR
2008
209views more  JMLR 2008»
13 years 10 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
LPAR
2010
Springer
13 years 8 months ago
On the Complexity of Model Expansion
Abstract. We study the complexity of model expansion (MX), which is the problem of expanding a given finite structure with additional relations to produce a finite model of a giv...
Antonina Kolokolova, Yongmei Liu, David G. Mitchel...
BMVC
2010
13 years 8 months ago
Incremental Model Selection for Detection and Tracking of Planar Surfaces
Man-made environments are abundant with planar surfaces which have attractive properties and are a prerequisite for a variety of vision tasks. This paper presents an incremental m...
Johann Prankl, Michael Zillich, Bastian Leibe, Mar...
ICASSP
2011
IEEE
13 years 1 months ago
On selecting the hyperparameters of the DPM models for the density estimation of observation errors
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
Asma Rabaoui, Nicolas Viandier, Juliette Marais, E...