It is well-known that supervised learning techniques such as linear discriminant analysis (LDA) often suffer from the so called small sample size problem when apply to solve face ...
Jie Wang, Konstantinos N. Plataniotis, Anastasios ...
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
Subspacefacerecognitionoftensuffersfromtwoproblems:(1)thetrainingsamplesetissmallcompared with the high dimensional feature vector; (2) the performance is sensitive to the subspace...
The paper proposes a method to keep the tracker robust to background clutters by online selecting discriminative features from a large feature space. Furthermore, the feature sele...
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...