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AUSAI
2008
Springer
13 years 9 months ago
Learning to Find Relevant Biological Articles without Negative Training Examples
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
Keith Noto, Milton H. Saier Jr., Charles Elkan
BIOID
2008
103views Biometrics» more  BIOID 2008»
13 years 9 months ago
Promoting Diversity in Gaussian Mixture Ensembles: An Application to Signature Verification
Abstract. Classifiers based on Gaussian mixture models are good performers in many pattern recognition tasks. Unlike decision trees, they can be described as stable classifier: a s...
Jonas Richiardi, Andrzej Drygajlo, Laetitia Todesc...
ECCV
2008
Springer
14 years 9 months ago
Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features
Abstract. Recently, impressive results have been reported for the detection of objects in challenging real-world scenes. Interestingly however, the underlying models vary greatly e...
Paul Schnitzspan, Mario Fritz, Bernt Schiele
CICLING
2010
Springer
13 years 10 months ago
Identification of Translationese: A Machine Learning Approach
This paper presents a machine learning approach to the study of translationese. The goal is to train a computer system to distinguish between translated and non-translated text, in...
Iustina Ilisei, Diana Inkpen, Gloria Corpas Pastor...
ICPR
2004
IEEE
14 years 8 months ago
A Consistency-Based Model Selection for One-Class Classification
Model selection in unsupervised learning is a hard problem. In this paper a simple selection criterion for hyperparameters in one-class classifiers (OCCs) is proposed. It makes us...
David M. J. Tax, Klaus-Robert Müller