In earlier work we have introduced and explored a variety of different probabilistic models for the problem of answering selectivity queries posed to large sparse binary data set...
This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...
Algebraic transformation and optimization techniques have been the method of choice in relational query execution, but applying them in OODBMS is difficult due to the complexity o...
Peter A. Boncz, Annita N. Wilschut, Martin L. Kers...
Background: In a high throughput setting, effective flow cytometry data analysis depends heavily on proper data preprocessing. While usual preprocessing steps of quality assessmen...
Greg Finak, Juan-Manuel Perez, Andrew Weng, Raphae...
In this paper, we tackle the problem of object detection and tracking in a new and challenging domain of wide area surveillance. This problem poses several challenges: large camera...