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» Optimizing Local Probability Models for Statistical Parsing
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CVPR
2007
IEEE
16 years 4 months ago
Combining Static Classifiers and Class Syntax Models for Logical Entity Recognition in Scanned Historical Documents
Class syntax can be used to 1) model temporal or locational evolvement of class labels of feature observation sequences, 2) correct classification errors of static classifiers if ...
Song Mao, Praveer Mansukhani, George R. Thoma
ANOR
2010
85views more  ANOR 2010»
15 years 2 months ago
Inventory management with partially observed nonstationary demand
Abstract. We consider a continuous-time model for inventory management with Markov modulated non-stationary demands. We introduce active learning by assuming that the state of the ...
Erhan Bayraktar, Michael Ludkovski
DAGM
1998
Springer
15 years 6 months ago
Discrete Mixture Models for Unsupervised Image Segmentation
This paper introduces a novel statistical mixture model for probabilistic clustering of histogram data and, more generally, for the analysis of discrete co occurrence data. Adoptin...
Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
EMNLP
2008
15 years 3 months ago
Stacking Dependency Parsers
We explore a stacked framework for learning to predict dependency structures for natural language sentences. A typical approach in graph-based dependency parsing has been to assum...
André F. T. Martins, Dipanjan Das, Noah A. ...
FOSSACS
2005
Springer
15 years 7 months ago
Branching Cells as Local States for Event Structures and Nets: Probabilistic Applications
We study the concept of choice for true concurrency models such as prime event structures and safe Petri nets. We propose a dynamic variation of the notion of cluster previously in...
Samy Abbes, Albert Benveniste