Given observed data and a collection of parameterized candidate models, a 1- confidence region in parameter space provides useful insight as to those models which are a good fit t...
Brent Bryan, H. Brendan McMahan, Chad M. Schafer, ...
Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...
The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
We consider the sparse grid combination technique for regression, which we regard as a problem of function reconstruction in some given function space. We use a regularised least ...
We consider the problem of finding duplicates in data streams. Duplicate detection in data streams is utilized in various applications including fraud detection. We develop a solu...