We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...
Understanding human emotions is one of the necessary skills for the computer to interact intelligently with human users. The most expressive way humans display emotions is through...
Ira Cohen, Nicu Sebe, Fabio Gagliardi Cozman, Marc...
This work proposes the exploration of student’s information through the use of Bayesian Networks. By using thisapproach we aim to model the uncertainty inherent to the studentâ€...
Object detection using Haar-like features is formulated as a maximum likelihood estimation. Object features are described by an arbitrary Bayesian Network (BN) of Haar-like featur...
The NLP systems often have low performances because they rely on unreliable and heterogeneous knowledge. We show on the task of non-anaphoric it identification how to overcome the...