We compare the practical performance of several recently proposed algorithms for active learning in the online classification setting. We consider two active learning algorithms (...
: Novelty detection, or anomaly detection, on temporal sequences has increasingly attracted attention from researchers in different areas. In this paper, we present a new framework...
Learning algorithms have enjoyed numerous successes in robotic control tasks. In problems with time-varying dynamics, online learning methods have also proved to be a powerful too...
This work presents GROUSE (Grassmanian Rank-One Update Subspace Estimation), an efficient online algorithm for tracking subspaces from highly incomplete observations. GROUSE requi...
The growing amount of online news posted on the WWW demands new algorithms that support topic detection, search, and navigation of news documents. This work presents an algorithm f...