—The machine learning and pervasive sensing technologies found in smart homes offer unprecedented opportunities for providing health monitoring and assistance to individuals expe...
Parisa Rashidi, Diane J. Cook, Lawrence B. Holder,...
Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...
This paper studies issues relating to the parameterization of probability distributions over binary data sets. Several such parameterizations of models for binary data are known, ...
David Buchman, Mark W. Schmidt, Shakir Mohamed, Da...
We investigate the prevalence and learning impact of different types of off-task behavior in classrooms where students are using intelligent tutoring software. We find that within...
Ryan Shaun Baker, Albert T. Corbett, Kenneth R. Ko...
In this paper, we exploit the problem of inferring images’ semantic concepts from community-contributed images and their associated noisy tags. To infer the concepts more accura...