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JMLR
2002
115views more  JMLR 2002»
14 years 9 months ago
PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
Matthias Seeger
NIPS
2001
14 years 11 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
MCS
2009
Springer
15 years 4 months ago
Improved Uniformity Enforcement in Stochastic Discrimination
There are a variety of methods for inducing predictive systems from observed data. Many of these methods fall into the field of study of machine learning. Some of the most effec...
Matthew Prior, Terry Windeatt
ICPR
2008
IEEE
15 years 3 months ago
Computer-aided grading of lymphangioleiomyomatosis (LAM) using HRCT
Lymphangioleiomyomatosis (LAM) is a multisystem disorder associated with proliferation of smooth muscle-like cells, which leads to destruction of lung parenchyma. Subjective gradi...
Jianhua Yao, Nilo Avila, Andrew Dwyer, Angelo M. T...
IJCAI
2003
14 years 10 months ago
Constructing Diverse Classifier Ensembles using Artificial Training Examples
Ensemble methods like bagging and boosting that combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity of the memb...
Prem Melville, Raymond J. Mooney