We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
Based on the correlation between expression and ontologydriven gene similarity, we incorporate functional annotations into gene expression clustering validation. A probabilistic f...
In [3] a probabilistic semantics for timed automata has been defined in order to rule out unlikely (sequences of) events. The qualitative model-checking problem for LTL propertie...
Nathalie Bertrand, Patricia Bouyer, Thomas Brihaye...
This paper addresses the problem of classifying human actions in a video sequence. A representation eigenspace approach based on the PCA algorithm is used to train the classifier...
Carlo Colombo, Dario Comanducci, Alberto Del Bimbo
The classification of graph based objects is an important challenge from a knowledge discovery standpoint and has attracted considerable attention recently. In this paper, we pres...
H. D. K. Moonesinghe, Hamed Valizadegan, Samah Jam...