Emergence of the web and online computing applications gave rise to rich large scale social activity data. One of the principal challenges then is to build models and understandin...
— To generate plans for collecting data for data mining, an important problem is information volatility during planning: the information needed by the planning system may change ...
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...