In this paper, a novel and efficient automatic image categorization system is proposed. This system integrates the MIL-based and global-featurebased SVMs for categorization. The IP...
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
During face-to-face conversation, the speaker’s head is continually in motion. These movements serve a variety of important communicative functions. Our goal is to develop a mod...