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ICASSP
2011
IEEE
12 years 9 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
13 years 9 days 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
14 years 7 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»
13 years 6 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»
13 years 5 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...