In recent years, there has been a growing interest in applying Bayesian networks and their extensions to reconstruct regulatory networks from gene expression data. Since the gene ...
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
We present a class of models that, via a simple construction,
enables exact, incremental, non-parametric, polynomial-time,
Bayesian inference of conditional measures. The approac...
Games are increasingly being used as educational tools, in part because they are presumed to enhance student motivation. We look at student motivation in games from the viewpoint o...
Amy Ogan, Vincent Aleven, Julia Kim, Christopher J...
In this paper, we attempt to automatically annotate the Penn Chinese Treebank with semantic dependency structure. Initially a small portion of the Penn Chinese Treebank was manual...
Jiajun Yan, David B. Bracewell, Fuji Ren, Shingo K...