Mixture models, such as Gaussian Mixture Model, have been widely used in many applications for modeling data. Gaussian mixture model (GMM) assumes that data points are generated fr...
We propose a novel approach for statistical risk modeling of network attacks that lets an operator perform risk analysis using a data model and an impact model on top of an attack ...
The convergence of embedded sensor systems and stream query processing suggests an important role for database techniques, in managing data that only partially – and often inacc...
Eirinaios Michelakis, Daisy Zhe Wang, Minos N. Gar...
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
Metadata management is an essential factor in data warehousing. In data warehousing environments, data is transformed and integrated into a single database from multiple autonomou...