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» Algorithms for Non-negative Matrix Factorization
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SDM
2012
SIAM
233views Data Mining» more  SDM 2012»
11 years 10 months ago
On Finding Joint Subspace Boolean Matrix Factorizations
Finding latent factors of the data using matrix factorizations is a tried-and-tested approach in data mining. But finding shared factors over multiple matrices is more novel prob...
Pauli Miettinen
SDM
2012
SIAM
281views Data Mining» more  SDM 2012»
11 years 10 months ago
Contextual Collaborative Filtering via Hierarchical Matrix Factorization
Matrix factorization (MF) has been demonstrated to be one of the most competitive techniques for collaborative filtering. However, state-of-the-art MFs do not consider contextual...
ErHeng Zhong, Wei Fan, Qiang Yang
SCIA
2009
Springer
132views Image Analysis» more  SCIA 2009»
14 years 2 months ago
Instant Action Recognition
In this paper, we present an efficient system for action recognition from very short sequences. For action recognition typically appearance and/or motion information of an action ...
Thomas Mauthner, Peter M. Roth, Horst Bischof
ISCAS
2008
IEEE
145views Hardware» more  ISCAS 2008»
14 years 2 months ago
Group learning using contrast NMF : Application to functional and structural MRI of schizophrenia
— Non-negative Matrix factorization (NMF) has increasingly been used as a tool in signal processing in the last couple of years. NMF, like independent component analysis (ICA) is...
Vamsi K. Potluru, Vince D. Calhoun
SIGIR
2012
ACM
11 years 10 months ago
Inferring missing relevance judgments from crowd workers via probabilistic matrix factorization
In crowdsourced relevance judging, each crowd worker typically judges only a small number of examples, yielding a sparse and imbalanced set of judgments in which relatively few wo...
Hyun Joon Jung, Matthew Lease