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ECAI
2010
Springer
13 years 9 months ago
Learning action effects in partially observable domains
We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...
Kira Mourão, Ronald P. A. Petrick, Mark Ste...
ADCM
2008
136views more  ADCM 2008»
13 years 8 months ago
Learning and approximation by Gaussians on Riemannian manifolds
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
Gui-Bo Ye, Ding-Xuan Zhou
AUTOMATICA
2006
103views more  AUTOMATICA 2006»
13 years 8 months ago
A universal iterative learning stabilizer for a class of MIMO systems
Design of iterative learning control (ILC) often requires some prior knowledge about a system's control matrix. In some applications, such as uncalibrated visual servoing, th...
Ping Jiang, Huadong Chen, Leon C. A. Bamforth
CVPR
2006
IEEE
14 years 10 months ago
Learning Distance Metrics with Contextual Constraints for Image Retrieval
Relevant Component Analysis (RCA) has been proposed for learning distance metrics with contextual constraints for image retrieval. However, RCA has two important disadvantages. On...
Steven C. H. Hoi, Wei Liu, Michael R. Lyu, Wei-Yin...
ECCV
2006
Springer
14 years 10 months ago
Learning Compositional Categorization Models
Abstract. This contribution proposes a compositional approach to visual object categorization of scenes. Compositions are learned from the Caltech 101 database1 intermediate abstra...
Björn Ommer, Joachim M. Buhmann