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CVPR
2005
IEEE
16 years 6 months ago
WaldBoost - Learning for Time Constrained Sequential Detection
: In many computer vision classification problems, both the error and time characterizes the quality of a decision. We show that such problems can be formalized in the framework of...
Jan Sochman, Jiri Matas
ASPLOS
2008
ACM
15 years 6 months ago
Learning from mistakes: a comprehensive study on real world concurrency bug characteristics
The reality of multi-core hardware has made concurrent programs pervasive. Unfortunately, writing correct concurrent programs is difficult. Addressing this challenge requires adva...
Shan Lu, Soyeon Park, Eunsoo Seo, Yuanyuan Zhou
KER
2007
90views more  KER 2007»
15 years 4 months ago
PLTOOL: A knowledge engineering tool for planning and learning
AI planning solves the problem of generating a correct and efficient ordered set of instantiated activities, from a knowledge base of generic actions, which when executed will tra...
Susana Fernández, Daniel Borrajo, Raquel Fu...
IJCNN
2006
IEEE
15 years 10 months ago
Optimal In-Place Learning and the Lobe Component Analysis
— It is difficult to map many existing learning algorithms onto biological networks because the former require a separate learning network. The computational basis of biological...
Juyang Weng, Nan Zhang 0002
ML
2010
ACM
151views Machine Learning» more  ML 2010»
15 years 2 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales