In automated text categorization, given a small number of labeled documents, it is very challenging, if not impossible, to build a reliable classifier that is able to achieve high...
Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu...
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
When a partitional structure is derived from a data set using a data mining algorithm, it is not unusual to have a different set of outcomes when it runs with a different order of...
In matching tasks in computer vision, and particularly in real-time tracking from video, there are generally strong priors available on absolute and relative correspondence locati...