Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
Efficiently finding Web services on the Web is a challenging issue in service-oriented computing. Currently, UDDI is a standard for publishing and discovery of Web services, and U...
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Object recognition is challenging due to high intra-class
variability caused, e.g., by articulation, viewpoint changes,
and partial occlusion. Successful methods need to strike a...