The goal of this paper is to show that generalizing the notion of support can be useful in extending association analysis to non-traditional types of patterns and non-binary data....
Michael Steinbach, Pang-Ning Tan, Hui Xiong, Vipin...
Class imbalance is a ubiquitous problem in supervised learning and has gained wide-scale attention in the literature. Perhaps the most prevalent solution is to apply sampling to t...
We study the tolerance of data structures to memory faults. We observe that many pointerbased data structures (e.g., linked lists, trees, etc.) are highly nonresilient to faults. ...
With the advent of high throughput technologies, feature selection has become increasingly important in a wide range of scientific disciplines. We propose a new feature selection ...
Abstract. An overview of the Time Series Knowledge Mining framework to discover knowledge in multivariate time series is given. A hierarchy of temporal patterns, which are not a pr...