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» Algorithms for Non-negative Matrix Factorization
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SDM
2012
SIAM
233views Data Mining» more  SDM 2012»
13 years 1 days 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»
13 years 1 days 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»
15 years 4 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»
15 years 4 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
99
Voted
SIGIR
2012
ACM
13 years 2 days 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