In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Using and extending a framework is a challenging task whose difficulty is exacerbated by the poor documentation that generally comes with the framework. Even in the presence of do...
This paper presents a specification-based approach for systematic testing of products from a software product line. Our approach uses specifications given as formulas in Alloy, a ...
Engin Uzuncaova, Daniel Garcia, Sarfraz Khurshid, ...
Software firms are increasingly distributing their software development effort across multiple locations. In this paper we present the results of a two year field study that inves...