This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
This paper presents an algorithm for inferring a Structured Hidden Markov Model (S-HMM) from a set of sequences. The S-HMMs are a sub-class of the Hierarchical Hidden Markov Model...
This paper reports on an approach which maps documents onto an ontology-based information space in order to provide support for machine-mediated communication. First, a composite ...
We present a system to recognize phrases based on perceptrons, and a global online learning algorithm to train them together. The recognition strategy applies learning in two laye...
This paper studies a framework for matching an unknown
number of corresponding structures in two images
(shapes), motivated by detecting objects in cluttered background
and lear...