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COGSR
2011
105views more  COGSR 2011»
13 years 5 months ago
Inductive rule learning on the knowledge level
We present an application of the analytical inductive programming system Igor to learning sets of recursive rules from positive experience. We propose that this approach can be us...
Ute Schmid, Emanuel Kitzelmann
SDM
2012
SIAM
216views Data Mining» more  SDM 2012»
12 years 20 days ago
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable
:  Feature Selection “Tomography” - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable George Forman HP Laboratories HPL-2010-19R1 Feature selection; ...
George Forman
DAGSTUHL
2006
13 years 11 months ago
Cognitive Vision Needs Attention to Link Sensing with Recognition
Abstract. "Cognitive computer vision is concerned with integration and control of vision systems using explicit but not necessarily symbolic models of context, situation and g...
John K. Tsotsos
CVPR
2004
IEEE
15 years 8 days ago
Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
ATAL
2007
Springer
14 years 4 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone