We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this framework, we motivate minimum entropy regulariza...
Abstract. We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kear...
In liquid chromatography-mass spectrometry (LC-MS) based expression proteomics, samples from different groups are analyzed comparatively in order to detect differences that can p...
Marius C. Codrea, Connie R. Jimenez, Sander R. Pie...
This work introduces a novel data mining scheme, spatial pyramid mining, to discover association rules at multiple resolutions in order to identify frequent spatial configuration...
This paper presents a general method for segmenting a vector valued sequence into an unknown number of subsequences where all data points from a subsequence can be represented wit...