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JAIR
2010
131views more  JAIR 2010»
13 years 7 months ago
Automatic Induction of Bellman-Error Features for Probabilistic Planning
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
Jia-Hong Wu, Robert Givan
IEICET
2007
114views more  IEICET 2007»
13 years 8 months ago
Analytic Optimization of Adaptive Ridge Parameters Based on Regularized Subspace Information Criterion
In order to obtain better learning results in supervised learning, it is important to choose model parameters appropriately. Model selection is usually carried out by preparing a ...
Shun Gokita, Masashi Sugiyama, Keisuke Sakurai
ICRA
2010
IEEE
227views Robotics» more  ICRA 2010»
13 years 6 months ago
Efficient multi-view object recognition and full pose estimation
We present an approach for efficiently recognizing all objects in a scene and estimating their full pose from multiple views. Our approach builds upon a state of the art single-vie...
Alvaro Collet, Siddhartha S. Srinivasa
PRL
2006
127views more  PRL 2006»
13 years 8 months ago
Ho-Kashyap classifier with early stopping for regularization
This paper focuses on linear classification using a fast and simple algorithm known as the Ho
Fabien Lauer, Gérard Bloch
DMIN
2007
186views Data Mining» more  DMIN 2007»
13 years 10 months ago
Cost-Sensitive Learning vs. Sampling: Which is Best for Handling Unbalanced Classes with Unequal Error Costs?
- The classifier built from a data set with a highly skewed class distribution generally predicts the more frequently occurring classes much more often than the infrequently occurr...
Gary M. Weiss, Kate McCarthy, Bibi Zabar