This paper explores the use of Bayesian online classifiers to classify text documents. Empirical results indicate that these classifiers are comparable with the best text classifi...
Existing online learning experiences lack the social dimension that characterizes learning in the real world. This social dimension extends beyond the traditional classroom into t...
We design and analyze interacting online algorithms for multitask classification that perform better than independent learners whenever the tasks are related in a certain sense. W...
Content analysis is often employed by teachers and research to analyse online discussion forums to serve various purposes such as assessment, evaluation, and educational research....
Andrew Kwok-Fai Lui, Siu Cheung Li, Sheung-On Choy
We present a competitive analysis of Bayesian learning algorithms in the online learning setting and show that many simple Bayesian algorithms (such as Gaussian linear regression ...