Conventional Binarization methods try to obtain optimal results based on the single image only. They make distinct diversity of binarization quality sometimes even for images of t...
We propose and evaluate a family of methods for converting classifier learning algorithms and classification theory into cost-sensitive algorithms and theory. The proposed conve...
Abstract. We propose to use semi-supervised learning methods to classify evaluative expressions, that is, tuples of subjects, their attributes, and evaluative words, that indicate ...
Abstract. We present a method to test a group of agents for (unwanted) emergent behavior by using techniques from learning of cooperative behavior. The general idea is to mimick us...
We present a method for learning to find English to Chinese transliterations on the Web. In our approach, proper nouns are expanded into new queries aimed at maximizing the probab...