We extend the PAC-Bayes theorem to the sample-compression setting where each classifier is represented by two independent sources of information: a compression set which consists ...
Many data mining applications can benefit from adapting existing classifiers to new data with shifted distributions. In this paper, we present Adaptive Support Vector Machine (Ada...
We address a new perceptual grouping algorithmfor aerial images, which employs a decision tree classifier and hierarchical multilevel grouping strategy an a bottom-up fashion. In ...
Abstract--A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generali...
The indirection of object accesses is a common theme for target domains as diverse as transparent distribution, persistence, and program instrumentation. Virtualizing accesses to ...
Phil McGachey, Antony L. Hosking, J. Eliot B. Moss