In this paper, we introduce a new class of data mining problems called learning from aggregate views. In contrast to the traditional problem of learning from a single table of tra...
Bee-Chung Chen, Lei Chen 0003, Raghu Ramakrishnan,...
Background: Information obtained from diverse data sources can be combined in a principled manner using various machine learning methods to increase the reliability and range of k...
Bolan Linghu, Evan S. Snitkin, Dustin T. Holloway,...
CoIL challenge 2000 was a supervised learning contest that attracted 43 entries. The authors of 29 entries later wrote explanations of their work. This paper discusses these repor...
Recognizing and analyzing change is an important human virtue because it enables us to anticipate future scenarios and thus allows us to act pro-actively. One approach to understa...
Abstract. Ensemble methods are popular learning methods that usually increase the predictive accuracy of a classifier though at the cost of interpretability and insight in the deci...