Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, dep...
In this paper we provide a fast, data-driven solution to the failing query problem: given a query that returns an empty answer, how can one relax the query's constraints so t...
We used Machine Learning (ML) methods to learn the best decision rules to distinguish normal brain aging from the earliest stages of dementia using subsamples of 198 normal and 244...
William Rodman Shankle, Subramani Mani, Michael J....
Program authorship attribution—identifying a programmer based on stylistic characteristics of code—has practical implications for detecting software theft, digital forensics, a...
Nathan E. Rosenblum, Xiaojin Zhu, Barton P. Miller
We propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. The approach relies on the idea of optimizing soft cascades. In particular, inst...