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ICML
2000
IEEE
16 years 7 months ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall
SDM
2009
SIAM
112views Data Mining» more  SDM 2009»
16 years 3 months ago
A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning.
Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern discovery algorithms employ exhaustive search. In this paper, we evaluat...
Frederik Janssen, Johannes Fürnkranz
ICRA
2009
IEEE
138views Robotics» more  ICRA 2009»
16 years 1 months ago
Which landmark is useful? Learning selection policies for navigation in unknown environments
Abstract— In general, a mobile robot that operates in unknown environments has to maintain a map and has to determine its own location given the map. This introduces significant...
Hauke Strasdat, Cyrill Stachniss, Wolfram Burgard
DAGM
2009
Springer
16 years 1 months ago
Active Structured Learning for High-Speed Object Detection
High-speed smooth and accurate visual tracking of objects in arbitrary, unstructured environments is essential for robotics and human motion analysis. However, building a system th...
Christoph H. Lampert, Jan Peters
209
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WMTE
2002
IEEE
15 years 11 months ago
Applying Wireless Technologies to Build a Highly Interactive Learning Environment
This study tries to apply wireless technologies to build a highly interactive environment. For this purpose, this study first identifies four types of interaction between the memb...
Tzu-Chien Liu, Hsue-Yie Wang, Jen-Kai Liang, Tak-W...