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» Learning Recursive Automata from Positive Examples
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ILP
2007
Springer
14 years 1 months ago
Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates
Statistical Relational Learning (SRL) combines the benefits of probabilistic machine learning approaches with complex, structured domains from Inductive Logic Programming (ILP). W...
Mark Goadrich, Jude W. Shavlik
CVPR
2010
IEEE
13 years 5 months ago
P-N learning: Bootstrapping binary classifiers by structural constraints
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
Zdenek Kalal, Jiri Matas, Krystian Mikolajczyk
NIPS
2004
13 years 9 months ago
Learning, Regularization and Ill-Posed Inverse Problems
Many works have shown that strong connections relate learning from examples to regularization techniques for ill-posed inverse problems. Nevertheless by now there was no formal ev...
Lorenzo Rosasco, Andrea Caponnetto, Ernesto De Vit...
IROS
2007
IEEE
141views Robotics» more  IROS 2007»
14 years 1 months ago
Laser tracking of human body motion using adaptive shape modeling
— In this paper we present a method for determining body orientation and pose information from laser scanner data using particle filtering with an adaptive modeling algorithm. A...
Dylan F. Glas, Takahiro Miyashita, Hiroshi Ishigur...
MICCAI
2004
Springer
14 years 8 months ago
Learning Coupled Prior Shape and Appearance Models for Segmentation
We present a novel framework for learning a joint shape and appearance model from a large set of un-labelled training examples in arbitrary positions and orientations. The shape an...
Xiaolei Huang, Zhiguo Li, Dimitris N. Metaxas