Abstract. Most classification methods assume that the samples are drawn independently and identically from an unknown data generating distribution, yet this assumption is violated ...
We introduce Hidden Process Models (HPMs), a class of probabilistic models for multivariate time series data. The design of HPMs has been motivated by the challenges of modeling h...
Rebecca Hutchinson, Tom M. Mitchell, Indrayana Rus...
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...
Feature selection is an important task in effective data mining. A new challenge to feature selection is the so-called “small labeled-sample problem” in which labeled data is...
As the use of virtualization and partitioning grows, it becomes possible to deploy a multi-tier web-based application with a variable amount of computing power. This introduces th...