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EKAW
2000
Springer
13 years 8 months ago
Informed Selection of Training Examples for Knowledge Refinement
Knowledge refinement tools rely on a representative set of training examples to identify and repair faults in a knowledge based system (KBS). In real environments it is often diffi...
Nirmalie Wiratunga, Susan Craw
ECML
2006
Springer
13 years 8 months ago
Improving Control-Knowledge Acquisition for Planning by Active Learning
Automatically acquiring control-knowledge for planning, as it is the case for Machine Learning in general, strongly depends on the training examples. In the case of planning, examp...
Raquel Fuentetaja, Daniel Borrajo
ICTAI
2002
IEEE
13 years 9 months ago
Updating a Hybrid Rule Base with New Empirical Source Knowledge
Neurules are a kind of hybrid rules that combine a symbolic (production rules) and a connectionist (adaline unit) representation. Each neurule is represented as an adaline unit. O...
Jim Prentzas, Ioannis Hatzilygeroudis, Athanasios ...
ECML
2007
Springer
13 years 10 months ago
Learning to Classify Documents with Only a Small Positive Training Set
Many real-world classification applications fall into the class of positive and unlabeled (PU) learning problems. In many such applications, not only could the negative training ex...
Xiaoli Li, Bing Liu, See-Kiong Ng
AWIC
2007
Springer
13 years 10 months ago
Improving Text Classification by Web Corpora
A major difficulty of supervised approaches for text classification is that they require a great number of training instances in order to construct an accurate classifier. This pap...
Rafael Guzmán-Cabrera, Manuel Montes-y-G&oa...
IRI
2008
IEEE
13 years 11 months ago
Compound record clustering algorithm for design pattern detection by decision tree learning
Recovering design patterns applied in a system can help refactoring the system. Machine learning algorithms have been successfully applied in mining data patterns. However, one of...
Jing Dong, Yongtao Sun, Yajing Zhao
CRV
2009
IEEE
115views Robotics» more  CRV 2009»
13 years 11 months ago
Learning Model Complexity in an Online Environment
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
Dan Levi, Shimon Ullman
CICLING
2009
Springer
13 years 11 months ago
Semi-supervised Word Sense Disambiguation Using the Web as Corpus
Abstract. As any other classification task, Word Sense Disambiguation requires a large number of training examples. These examples, which are easily obtained for most of the tasks,...
Rafael Guzmán-Cabrera, Paolo Rosso, Manuel ...
ICML
2005
IEEE
14 years 5 months ago
Explanation-Augmented SVM: an approach to incorporating domain knowledge into SVM learning
We introduce a novel approach to incorporating domain knowledge into Support Vector Machines to improve their example efficiency. Domain knowledge is used in an Explanation Based ...
Qiang Sun, Gerald DeJong
ICCV
2003
IEEE
14 years 6 months ago
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...
Fei-Fei Li 0002, Robert Fergus, Pietro Perona