The problem of incomplete data--i.e., data with missing or unknown values--in multi-way arrays is ubiquitous in biomedical signal processing, network traffic analysis, bibliometri...
Evrim Acar, Tamara G. Kolda, Daniel M. Dunlavy, Mo...
Semistructured data occur in situations where information lacks a homogeneous structure and is incomplete. Yet, up to now the incompleteness of information has not been re ected b...
Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged a...
Incomplete databases, that is, databases that are missing data, are present in many research domains. It is important to derive techniques to access these databases efficiently. We...
Guadalupe Canahuate, Michael Gibas, Hakan Ferhatos...
There is a growing wealth of data describing networks of various types, including social networks, physical networks such as transportation or communication networks, and biologic...