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...
In crowdsourced relevance judging, each crowd worker typically judges only a small number of examples, yielding a sparse and imbalanced set of judgments in which relatively few wo...
In order to develop intelligent systems that attain the trust of their users, it is important to understand how users perceive such systems and develop those perceptions over time...
Joe Tullio, Anind K. Dey, Jason Chalecki, James Fo...
A Classification Association Rule (CAR), a common type of mined knowledge in Data Mining, describes an implicative co-occurring relationship between a set of binary-valued data-att...
This paper is devoted to explore media correlation and media synchronization in a composite multimedia document, the so-called navigated hypermedia document in our language learni...