We address the problem of evaluating the risk of a given model accurately at minimal labeling costs. This problem occurs in situations in which risk estimates cannot be obtained f...
Christoph Sawade, Niels Landwehr, Steffen Bickel, ...
We introduce a novel active-learning scenario in which a user wants to work with a learning algorithm to identify useful anomalies. These are distinguished from the traditional st...
Abstract. In the last years, techniques for activity recognition have attracted increasing attention. Among many applications, a special interest is in the pervasive e-Health domai...
The general approach for automatically driving data collection using information from previously acquired data is called active learning. Traditional active learning addresses the...
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...