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ICPR
2010
IEEE
13 years 12 months ago
Bayesian Inference for Nonnegative Matrix Factor Deconvolution Models
In this paper we develop a probabilistic interpretation and a full Bayesian inference for non-negative matrix deconvolution (NMFD) model. Our ultimate goal is unsupervised extract...
Serap Kirbiz, Ali Taylan Cemgil, Bilge Gunsel
ICDM
2009
IEEE
131views Data Mining» more  ICDM 2009»
13 years 2 months ago
Unified Solution to Nonnegative Data Factorization Problems
In this paper, we restudy the non-convex data factorization problems (regularized or not, unsupervised or supervised), where the optimization is confined in the nonnegative orthan...
Xiaobai Liu, Shuicheng Yan, Jun Yan, Hai Jin
ICDM
2010
IEEE
146views Data Mining» more  ICDM 2010»
13 years 2 months ago
One-Class Matrix Completion with Low-Density Factorizations
Consider a typical recommendation problem. A company has historical records of products sold to a large customer base. These records may be compactly represented as a sparse custom...
Vikas Sindhwani, Serhat Selcuk Bucak, Jianying Hu,...
ISCAS
2008
IEEE
217views Hardware» more  ISCAS 2008»
13 years 11 months ago
Approximate L0 constrained non-negative matrix and tensor factorization
— Non-negative matrix factorization (NMF), i.e. V ≈ WH where both V, W and H are non-negative has become a widely used blind source separation technique due to its part based r...
Morten Mørup, Kristoffer Hougaard Madsen, L...
IPMI
2011
Springer
12 years 8 months ago
Nonnegative Factorization of Diffusion Tensor Images and Its Applications
This paper proposes a novel method for computing linear basis images from tensor-valued image data. As a generalization of the nonnegative matrix factorization, the proposed method...
Yuchen Xie, Jeffrey Ho, Baba C. Vemuri