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» Preference learning with Gaussian processes
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ICIP
2007
IEEE
14 years 9 months ago
Unsupervised Modeling of Object Tracks for Fast Anomaly Detection
A key goal of far-field activity analysis is to learn the usual pattern of activity in a scene and to detect statistically anomalous behavior. We propose a method for unsupervised...
Tomas Izo, W. Eric L. Grimson
NIPS
2001
13 years 8 months ago
Covariance Kernels from Bayesian Generative Models
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...
Matthias Seeger
ICML
2005
IEEE
14 years 8 months ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski
IPSN
2010
Springer
14 years 2 months ago
Bayesian optimization for sensor set selection
We consider the problem of selecting an optimal set of sensors, as determined, for example, by the predictive accuracy of the resulting sensor network. Given an underlying metric ...
Roman Garnett, Michael A. Osborne, Stephen J. Robe...
JMS
2010
90views more  JMS 2010»
13 years 5 months ago
Prediction of Clinical Conditions after Coronary Bypass Surgery using Dynamic Data Analysis
This work studies the impact of using dynamic information as features in a machine learning algorithm for the prediction task of classifying critically ill patients in two classes ...
Kristien Van Loon, Fabián Güiza, Geert...