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JMLR
2008
104views more  JMLR 2008»
13 years 5 months ago
Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2
In this paper, the naive credal classifier, which is a set-valued counterpart of naive Bayes, is extended to a general and flexible treatment of incomplete data, yielding a new cl...
Giorgio Corani, Marco Zaffalon
JMLR
2008
139views more  JMLR 2008»
13 years 5 months ago
Regularization on Graphs with Function-adapted Diffusion Processes
Harmonic analysis and diffusion on discrete data has been shown to lead to state-of-theart algorithms for machine learning tasks, especially in the context of semi-supervised and ...
Arthur D. Szlam, Mauro Maggioni, Ronald R. Coifman
JMLR
2008
117views more  JMLR 2008»
13 years 5 months ago
Active Learning by Spherical Subdivision
We introduce a computationally feasible, "constructive" active learning method for binary classification. The learning algorithm is initially formulated for separable cl...
Falk-Florian Henrich, Klaus Obermayer
JMLR
2008
108views more  JMLR 2008»
13 years 5 months ago
A Recursive Method for Structural Learning of Directed Acyclic Graphs
In this paper, we propose a recursive method for structural learning of directed acyclic graphs (DAGs), in which a problem of structural learning for a large DAG is first decompos...
Xianchao Xie, Zhi Geng
JMLR
2008
83views more  JMLR 2008»
13 years 5 months ago
Evidence Contrary to the Statistical View of Boosting
The statistical perspective on boosting algorithms focuses on optimization, drawing parallels with maximum likelihood estimation for logistic regression. In this paper we present ...
David Mease, Abraham Wyner