We propose a feature selection method that constructs each new feature by analysis of tight error clusters. This is a greedy, time-efficient forward selection algorithm that itera...
The widespread presence of errors in spreadsheets is now well-established. Quite a few methodological and software approaches have been suggested as ways to reduce spreadsheet err...
We introduce a concrete semantics for floating-point operations which describes the propagation of roundoff errors throughout a calculation. This semantics is used to assert the co...
Traditionally computer vision and pattern recognition algorithms are evaluated by measuring differences between final interpretations and ground truth. These black-box evaluations ...
Richard Zanibbi, Dorothea Blostein, James R. Cordy
Many static and dynamic analyses have been developed to improve program quality. Several of them are well known and widely used in practice. It is not entirely clear, however, how ...