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AAAI
2006
14 years 11 months ago
Semi-supervised Multi-label Learning by Constrained Non-negative Matrix Factorization
We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key a...
Yi Liu, Rong Jin, Liu Yang
COST
2010
Springer
131views Multimedia» more  COST 2010»
14 years 4 months ago
Understanding Parent-Infant Behaviors Using Non-negative Matrix Factorization
Abstract. There are considerable differences among infants in the quality of interaction with their parents. These differences depend especially on the infants development which af...
Ammar Mahdhaoui, Mohamed Chetouani
SADM
2008
178views more  SADM 2008»
14 years 9 months ago
Fast Projection-Based Methods for the Least Squares Nonnegative Matrix Approximation Problem
: Nonnegative matrix approximation (NNMA) is a popular matrix decomposition technique that has proven to be useful across a diverse variety of fields with applications ranging from...
Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon
82
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ECCV
2006
Springer
15 years 11 months ago
Controlling Sparseness in Non-negative Tensor Factorization
Non-negative tensor factorization (NTF) has recently been proposed as sparse and efficient image representation (Welling and Weber, Patt. Rec. Let., 2001). Until now, sparsity of t...
Matthias Heiler, Christoph Schnörr
FLAIRS
2010
14 years 12 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...