Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
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...
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...
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...
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...