This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...
In this paper we present an empirical study of object category recognition using generalized samples and a set of sequential tests. We study 33 categories, each consisting of a sm...
Liang Lin, Shaowu Peng, Jake Porway, Song Chun Zhu...
d Abstract) F. Blanchet-Sadri1 , N.C. Brownstein2 , and Justin Palumbo3 1 Department of Computer Science, University of North Carolina, P.O. Box 26170, Greensboro, NC 27402–6170,...
Francine Blanchet-Sadri, N. C. Brownstein, Justin ...
In this paper we are concerned with the problem of learning how to solve planning problems in one domain given a number of solved instances. This problem is formulated as the probl...
Uncertainty processing methods are analysed from the viewpoint of their sensitivity to small variations of certainty factors. The analysis makes use of the algebraic theory which ...