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» An Integrated Instance-Based Learning Algorithm
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ICML
2009
IEEE
15 years 10 months ago
Boosting with structural sparsity
Despite popular belief, boosting algorithms and related coordinate descent methods are prone to overfitting. We derive modifications to AdaBoost and related gradient-based coordin...
John Duchi, Yoram Singer
ICML
2006
IEEE
15 years 10 months ago
Fast particle smoothing: if I had a million particles
We propose efficient particle smoothing methods for generalized state-spaces models. Particle smoothing is an expensive O(N2 ) algorithm, where N is the number of particles. We ov...
Mike Klaas, Mark Briers, Nando de Freitas, Arnaud ...
PAMI
2006
215views more  PAMI 2006»
14 years 9 months ago
Bayesian Feature and Model Selection for Gaussian Mixture Models
We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of ...
Constantinos Constantinopoulos, Michalis K. Titsia...
CVPR
2005
IEEE
15 years 11 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
ML
2007
ACM
130views Machine Learning» more  ML 2007»
14 years 9 months ago
Interactive learning of node selecting tree transducer
We develop new algorithms for learning monadic node selection queries in unranked trees from annotated examples, and apply them to visually interactive Web information extraction. ...
Julien Carme, Rémi Gilleron, Aurélie...