In this paper, we present a stream-based mining algorithm for online anomaly prediction. Many real-world applications such as data stream analysis requires continuous cluster opera...
Abstract. We present a novel computational framework for characterizing signal in brain images via nonlinear pairing of critical values of the signal. Among the astronomically larg...
Moo K. Chung, Vikas Singh, Peter T. Kim, Kim M....
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
This paper describes a new methodology and associated theoretical analysis for rapid and accurate extraction of activation regions from functional MRI data. Most fMRI data analysi...
Aarti Singh, Rebecca Willett, Robert Nowak, Zachar...
Contemporary work increasingly involves interacting with strangers in technology-mediated environments. In this context, we come to rely on digital artifacts to infer characterist...
N. Sadat Shami, Kate Ehrlich, Geri Gay, Jeffrey T....