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ICANN
2009
Springer
15 years 10 months ago
Constrained Learning Vector Quantization or Relaxed k-Separability
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
Marek Grochowski, Wlodzislaw Duch
CVPR
2004
IEEE
16 years 8 months ago
An Unsupervised, Online Learning Framework for Moving Object Detection
Object detection with a learned classifier has been applied successfully to difficult tasks such as detecting faces and pedestrians. Systems using this approach usually learn the ...
Vinod Nair, James J. Clark
CVPR
2007
IEEE
16 years 8 months ago
A Bio-inspired Learning Approach for the Classification of Risk Zones in a Smart Space
Learning from experience is a basic task of human brain that is not yet fulfilled satisfactorily by computers. Therefore, in recent years to cope with this issue, bio-inspired app...
Alessio Dore, Matteo Pinasco, Carlo S. Regazzoni
ECCV
2008
Springer
16 years 8 months ago
Beyond Nouns: Exploiting Prepositions and Comparative Adjectives for Learning Visual Classifiers
Learning visual classifiers for object recognition from weakly labeled data requires determining correspondence between image regions and semantic object classes. Most approaches u...
Abhinav Gupta, Larry S. Davis
180
Voted
ALT
2006
Springer
16 years 3 months ago
Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement Learning
Abstract. Recently, some non-regular subclasses of context-free grammars have been found to be efficiently learnable from positive data. In order to use these efficient algorithms ...
Takeshi Shibata, Ryo Yoshinaka, Takashi Chikayama