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» Scalable Tensor Factorizations with Missing Data
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SDM
2010
SIAM
204views Data Mining» more  SDM 2010»
14 years 9 days ago
Scalable Tensor Factorizations with Missing Data
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...
CORR
2010
Springer
255views Education» more  CORR 2010»
13 years 11 months ago
Scalable Tensor Factorizations for Incomplete Data
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...
ICDM
2010
IEEE
166views Data Mining» more  ICDM 2010»
13 years 8 months ago
Exponential Family Tensor Factorization for Missing-Values Prediction and Anomaly Detection
In this paper, we study probabilistic modeling of heterogeneously attributed multi-dimensional arrays. The model can manage the heterogeneity by employing an individual exponential...
Kohei Hayashi, Takashi Takenouchi, Tomohiro Shibat...
ICDM
2008
IEEE
141views Data Mining» more  ICDM 2008»
14 years 5 months ago
Scalable Tensor Decompositions for Multi-aspect Data Mining
Modern applications such as Internet traffic, telecommunication records, and large-scale social networks generate massive amounts of data with multiple aspects and high dimensiona...
Tamara G. Kolda, Jimeng Sun
AAAI
2008
14 years 1 months ago
Multi-HDP: A Non Parametric Bayesian Model for Tensor Factorization
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...
Ian Porteous, Evgeniy Bart, Max Welling