Activity recognition based on data from mobile wearable devices is becoming an important application area for machine learning. We propose a novel approach based on a combination ...
In this paper, we study cost-sensitive semi-supervised learning where many of the training examples are unlabeled and different misclassification errors are associated with unequa...
We describe a recommender system which uses a unique combination of content-based and collaborative methods to suggest items of interest to users, and also to learn and exploit it...
This paper presents a new boosting (arcing) algorithm called POCA, Parallel Online Continuous Arcing. Unlike traditional boosting algorithms (such as Arc-x4 and Adaboost), that co...
Jesse A. Reichler, Harlan D. Harris, Michael A. Sa...
Selective sampling, a form of active learning, reduces the cost of labeling training data by asking only for the labels of the most informative unlabeled examples. We introduce a ...