Defect density and defect prediction are essential for efficient resource allocation in software evolution. In an empirical study we applied data mining techniques for value seri...
We present an efficient protocol for privacy-preserving evaluation of diagnostic programs, represented as binary decision trees or branching programs. The protocol applies a bran...
Justin Brickell, Donald E. Porter, Vitaly Shmatiko...
Boosting is a simple yet powerful modeling technique that is used in many machine learning and data mining related applications. In this paper, we propose a novel scale-space based...
Multiagent systems for mobile and pervasive computing should extensively exploit contextual information both to adapt to user needs and to enable autonomic behavior. This raises th...
Gabriella Castelli, Marco Mamei, Franco Zambonelli
The goal in domain adaptation is to train a model using labeled data sampled from a domain different from the target domain on which the model will be deployed. We exploit unlabel...