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» Nonnegative Tucker Decomposition
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CVPR
2008
IEEE
14 years 7 months ago
Non-negative graph embedding
We introduce a general formulation, called non-negative graph embedding, for non-negative data decomposition by integrating the characteristics of both intrinsic and penalty graph...
Jianchao Yang, Shuicheng Yan, Yun Fu, Xuelong Li, ...
ICASSP
2011
IEEE
12 years 9 months ago
Multi-channel EEG compression based on matrix and tensor decompositions
Compression schemes for EEG signals are developed based on matrix and tensor decomposition. Various ways to arrange EEG signals into matrices and tensors are explored, and several...
Justin Dauwels, K. Srinivasan, M. Ramasubba Reddy,...
FLAIRS
2010
13 years 8 months ago
Correlating Shape and Functional Properties Using Decomposition Approaches
In this paper, we propose the application of standard decomposition approaches to find local correlations in multimodal data. In a test scenario, we apply these methods to correla...
Daniel Dornbusch, Robert Haschke, Stefan Menzel, H...
ICCV
2005
IEEE
14 years 7 months ago
Sparse Image Coding Using a 3D Non-Negative Tensor Factorization
We introduce an algorithm for a non-negative 3D tensor factorization for the purpose of establishing a local parts feature decomposition from an object class of images. In the pas...
Tamir Hazan, Simon Polak, Amnon Shashua
CORR
2004
Springer
152views Education» more  CORR 2004»
13 years 5 months ago
Non-negative matrix factorization with sparseness constraints
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been a...
Patrik O. Hoyer