We consider PAC-learning where the distribution is known to the student. The problem addressed here is characterizing when learnability with respect to distribution D1 implies lea...
Adaptivity has been an important research topic during the past two decades, especially in the field of e-learning. This paper deals with the question of whether and to what exte...
Bagging and boosting reduce error by changing both the inputs and outputs to form perturbed training sets, grow predictors on these perturbed training sets and combine them. A que...
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
We address the e-rulemaking problem of reducing the manual labor required to analyze public comment sets. In current and previous work, for example, text categorization techniques...