Online learning algorithms have recently risen to prominence due to their strong theoretical guarantees and an increasing number of practical applications for large-scale data ana...
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
An interesting issue in moving objects databases is to find similar trajectories of moving objects. Previous work on this topic focuses on movement patterns (trajectories with tim...
The k-nearest-neighbor rule is one of the most attractive pattern classification algorithms. In practice, the choice of k is determined by the cross-validation method. In this wor...
We address the problem of automatically acquiring case frame patterns (selectional patterns) from large corpus data. In particular, we l)ropose a method of learning dependencies b...