This paper describes our work in usage pattern analysis and development of a latent semantic analysis framework for interpreting multimodal user input consisting speech and pen ge...
In the present study, using event-related functional magnetic resonance imaging, we investigated a group of participants on a grammaticality classification task after they had bee...
Karl Magnus Petersson, Christian Forkstam, Martin ...
We introduce a novel machine learning framework based on recursive autoencoders for sentence-level prediction of sentiment label distributions. Our method learns vector space repr...
Richard Socher, Jeffrey Pennington, Eric H. Huang,...
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
The Bayesian framework offers a number of techniques for inferring an individual's knowledge state from evidence of mastery of concepts or skills. A typical application where ...