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138
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STACS
1999
Springer
15 years 9 months ago
A Complete and Tight Average-Case Analysis of Learning Monomials
Abstract. We advocate to analyze the average complexity of learning problems. An appropriate framework for this purpose is introduced. Based on it we consider the problem of learni...
Rüdiger Reischuk, Thomas Zeugmann
COGSCI
2007
99views more  COGSCI 2007»
15 years 4 months ago
Language Evolution by Iterated Learning With Bayesian Agents
Languages are transmitted from person to person and generation to generation via a process of iterated learning: people learn a language from other people who once learned that la...
Thomas L. Griffiths, Michael L. Kalish
142
Voted
ICML
2006
IEEE
16 years 5 months ago
Iterative RELIEF for feature weighting
RELIEF is considered one of the most successful algorithms for assessing the quality of features. In this paper, we propose a set of new feature weighting algorithms that perform s...
Yijun Sun, Jian Li
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
16 years 5 months ago
Exploiting unlabeled data in ensemble methods
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Kristin P. Bennett, Ayhan Demiriz, Richard Maclin
PRICAI
2000
Springer
15 years 8 months ago
A Comparative Study on Chinese Text Categorization Methods
Abstract. This paper reports our comparative evaluation of three machine learning methods on Chinese text categorization. Whereas a wide range of methods have been applied to Engli...
Ji He, Ah-Hwee Tan, Chew Lim Tan