We study the problem of online learning of multiple tasks in parallel. On each online round, the algorithm receives an instance and makes a prediction for each one of the parallel ...
The negotiation of what is to count as mutually acceptable collaborative knowledge is difficult to conduct when participants cannot interact face-to-face. We review certain relate...
Monaural speech segregation in reverberant environments is a very difficult problem. We develop a supervised learning approach by proposing an objective function that directly rel...
Open learner models (OLM) are learner models that are accessible to the learner they represent. Many examples now exist, often with the aim of prompting learner reflection on their...
Inspired by “GoogleTM Sets” and Bayesian sets, we consider the problem of retrieving complex objects and relations among them, i.e., ground atoms from a logical concept, given...