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» TD Models: Modeling the World at a Mixture of Time Scales
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ICML
2005
IEEE
14 years 5 months ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
TMI
2010
175views more  TMI 2010»
12 years 11 months ago
Spatially Adaptive Mixture Modeling for Analysis of fMRI Time Series
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In [1, 2...
Thomas Vincent, Laurent Risser, Philippe Ciuciu
NIPS
2001
13 years 6 months ago
A Parallel Mixture of SVMs for Very Large Scale Problems
Support Vector Machines (SVMs) are currently the state-of-the-art models for many classication problems but they suer from the complexity of their training algorithm which is at l...
Ronan Collobert, Samy Bengio, Yoshua Bengio
CSDA
2010
165views more  CSDA 2010»
13 years 5 months ago
A two-component Weibull mixture to model early and late mortality in a Bayesian framework
A two component parametric mixture is proposed to model survival after an invasive treatment, when patients may experience different hazards regimes: a risk of early mortality dir...
Alessio Farcomeni, Alessandra Nardi