Abstract. Model selection is an important problem in statistics, machine learning, and data mining. In this paper, we investigate the problem of enabling multiple parties to perfor...
Abstract— This paper proposes an approach to learn subjectindependent P300 models for EEG-based brain-computer interfaces. The P300 models are first learned using a pool of exis...
In sensor networks, privacy can be addressed in different levels of the network stack and at different points of the information flow. This paper presents an application level sche...
Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan
There are several parallel programming models available for numerical computations at different levels of expressibility and ease of use. For the development of new domain speci...