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ICASSP
2011
IEEE
14 years 1 months ago
Co-clustering as multilinear decomposition with sparse latent factors
The K-means clustering problem seeks to partition the columns of a data matrix in subsets, such that columns in the same subset are ‘close’ to each other. The co-clustering pr...
Evangelos E. Papalexakis, Nicholas D. Sidiropoulos
CSDA
2011
14 years 4 months ago
Hierarchical multilinear models for multiway data
Reduced-rank decompositions provide descriptions of the variation among the elements of a matrix or array. In such decompositions, the elements of an array are expressed as produc...
Peter D. Hoff
CVPR
2007
IEEE
15 years 11 months ago
Nonnegative Tucker Decomposition
Nonnegative tensor factorization (NTF) is a recent multiway (multilinear) extension of nonnegative matrix factorization (NMF), where nonnegativity constraints are imposed on the C...
Yong-Deok Kim, Seungjin Choi
SDM
2010
SIAM
195views Data Mining» more  SDM 2010»
14 years 11 months ago
MACH: Fast Randomized Tensor Decompositions
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...
Charalampos E. Tsourakakis
CORR
2010
Springer
255views Education» more  CORR 2010»
14 years 9 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...