The problem of missing data is ubiquitous in domains such as biomedical signal processing, network traffic analysis, bibliometrics, social network analysis, chemometrics, computer...
Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda, Mo...
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...
In this paper, we study probabilistic modeling of heterogeneously attributed multi-dimensional arrays. The model can manage the heterogeneity by employing an individual exponential...
Modern applications such as Internet traffic, telecommunication records, and large-scale social networks generate massive amounts of data with multiple aspects and high dimensiona...
Matrix factorization algorithms are frequently used in the machine learning community to find low dimensional representations of data. We introduce a novel generative Bayesian pro...