Tensors naturally model many real world processes which generate multi-aspect data. Such processes appear in many different research disciplines, e.g, chemometrics, computer visio...
Large graph databases are commonly collected and analyzed in numerous domains. For reasons related to either space efficiency or for privacy protection (e.g., in the case of socia...
We introduce a novel Bayesian framework for hybrid community discovery in graphs. Our framework, HCDF (short for Hybrid Community Discovery Framework), can effectively incorporate...
Keith Henderson, Tina Eliassi-Rad, Spiros Papadimi...
A highly skewed microdata contains some sensitive attribute values that occur far more frequently than others. Such data violates the "eligibility condition" assumed by ...
Yabo Xu, Ke Wang, Ada Wai-Chee Fu, Raymond Chi-Win...
We present Confidence-based Feature Acquisition (CFA), a novel supervised learning method for acquiring missing feature values when there is missing data at both training and test...
Marie desJardins, James MacGlashan, Kiri L. Wagsta...