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» Sampling Methods for Unsupervised Learning
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ICML
2005
IEEE
16 years 3 months ago
Compact approximations to Bayesian predictive distributions
We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...
Edward Snelson, Zoubin Ghahramani
TMI
2010
175views more  TMI 2010»
14 years 9 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
2008
15 years 3 months ago
QUIC-SVD: Fast SVD Using Cosine Trees
The Singular Value Decomposition is a key operation in many machine learning methods. Its computational cost, however, makes it unscalable and impractical for applications involvi...
Michael P. Holmes, Alexander G. Gray, Charles Lee ...
CIDM
2007
IEEE
15 years 8 months ago
Prediction of Abnormal Behaviors for Intelligent Video Surveillance Systems
–The OBSERVER is a video surveillance system that detects and predicts abnormal behaviors aiming at the intelligent surveillance concept. The system acquires color images from a ...
Duarte Duque, Henrique Santos, Paulo Cortez
NECO
2011
14 years 9 months ago
Least Squares Estimation Without Priors or Supervision
Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...
Martin Raphan, Eero P. Simoncelli