The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
Many testing and analysis techniques use finite state models to validate and verify the quality of software systems. Since the specification of such models is complex and timecons...
Clio is an existing schema-mapping tool that provides user-friendly means to manage and facilitate the complex task of transformation and integration of heterogeneous data such as...
Haifeng Jiang, Howard Ho, Lucian Popa, Wook-Shin H...
In recent years researchers have developed a wide range of powerful automated reasoning systems. We have leveraged these systems to build Jahob, a program specification, analysis, ...