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» Learning Models for Object Recognition
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JMLR
2008
95views more  JMLR 2008»
14 years 10 months ago
Learning Similarity with Operator-valued Large-margin Classifiers
A method is introduced to learn and represent similarity with linear operators in kernel induced Hilbert spaces. Transferring error bounds for vector valued large-margin classifie...
Andreas Maurer
ICANN
2005
Springer
15 years 3 months ago
Learning Features of Intermediate Complexity for the Recognition of Biological Motion
Humans can recognize biological motion from strongly impoverished stimuli, like point-light displays. Although the neural mechanism underlying this robust perceptual process have n...
Rodrigo Sigala, Thomas Serre, Tomaso Poggio, Marti...
AAAI
2007
15 years 13 days ago
Autonomous Development of a Grounded Object Ontology by a Learning Robot
We describe how a physical robot can learn about objects from its own autonomous experience in the continuous world. The robot identifies statistical regularities that allow it t...
Joseph Modayil, Benjamin Kuipers
JMLR
2006
103views more  JMLR 2006»
14 years 10 months ago
Pattern Recognition for Conditionally Independent Data
In this work we consider the task of relaxing the i.i.d. assumption in pattern recognition (or classification), aiming to make existing learning algorithms applicable to a wider r...
Daniil Ryabko
ICASSP
2009
IEEE
15 years 4 months ago
Using collective information in semi-supervised learning for speech recognition
Training accurate acoustic models typically requires a large amount of transcribed data, which can be expensive to obtain. In this paper, we describe a novel semi-supervised learn...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...