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» Learning hierarchical task networks by observation
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ECML
2006
Springer
13 years 11 months ago
Efficient Non-linear Control Through Neuroevolution
Abstract. Many complex control problems are not amenable to traditional controller design. Not only is it difficult to model real systems, but often it is unclear what kind of beha...
Faustino J. Gomez, Jürgen Schmidhuber, Risto ...
IJAR
2010
130views more  IJAR 2010»
13 years 6 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki
CVPR
2010
IEEE
14 years 3 months ago
Detecting and Parsing Architecture at City Scale from Range Data
We present a method for detecting and parsing buildings from unorganized 3D point clouds into a compact, hierarchical representation that is useful for high-level tasks. The input...
Alexander Toshev, Philippos Mordohai, Ben Taskar
HICSS
2003
IEEE
95views Biometrics» more  HICSS 2003»
14 years 24 days ago
Matching Needs - Application Service Providing for Asynchronous Learning Networks
Universities have severe difficulties in using elearning applications successfully due to organizational problems to provide them. Providing a web-based learning environment is an...
Wolf-Gideon Bleek, Iver Jackewitz, Bernd Pape
IJCNN
2008
IEEE
14 years 1 months ago
Learning to select relevant perspective in a dynamic environment
— When an agent observes its environment, there are two important characteristics of the perceived information. One is the relevance of information and the other is redundancy. T...
Zhihui Luo, David A. Bell, Barry McCollum, Qingxia...