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DAGM
2008
Springer
14 years 11 months ago
An Evolutionary Approach for Learning Motion Class Patterns
This article presents a genetic learning algorithm to derive discrete patterns that can be used for classification and retrieval of 3D motion capture data. Based on boolean motion ...
Meinard Müller, Bastian Demuth, Bodo Rosenhah...
AAAI
2006
14 years 11 months ago
kFOIL: Learning Simple Relational Kernels
A novel and simple combination of inductive logic programming with kernel methods is presented. The kFOIL algorithm integrates the well-known inductive logic programming system FO...
Niels Landwehr, Andrea Passerini, Luc De Raedt, Pa...
APIN
2010
108views more  APIN 2010»
14 years 10 months ago
A low variance error boosting algorithm
Abstract. This paper introduces a robust variant of AdaBoost, cwAdaBoost, that uses weight perturbation to reduce variance error, and is particularly effective when dealing with da...
Ching-Wei Wang, Andrew Hunter
IJBIDM
2006
78views more  IJBIDM 2006»
14 years 9 months ago
Appraisal of companies with Bayesian networks
: Appraisal of companies is an important business activity. We mainly apply Bayesian networks for this classification task for Japanese electric company data. Firstly, few standard...
Priyantha Wijayatunga, Shigeru Mase, Masanori Naka...
JFR
2006
77views more  JFR 2006»
14 years 9 months ago
Learning from examples in unstructured, outdoor environments
In this paper, we present a multi-pronged approach to the "Learning from Example" problem. In particular, we present a framework for integrating learning into a standard...
Jie Sun, Tejas R. Mehta, David Wooden, Matthew Pow...