Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
This paper considers a method for learning a distance metric in a fingerprinting system which identifies a query content by measuring the distance between the fingerprint of th...
— This paper demonstrates a learning mechanism for complex tasks. Such tasks may be inherently expensive to learn in terms of training time and/or cost of obtaining each training...
In this paper we describe a method to learn parameters
which govern pedestrian motion by observing video
data. Our learning framework is based on variational
mode learning and a...