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» Nonnegative Matrix Factorization in Polynomial Feature Space
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ACL
2004
13 years 9 months ago
Aligning words using matrix factorisation
Aligning words from sentences which are mutual translations is an important problem in different settings, such as bilingual terminology extraction, Machine Translation, or projec...
Cyril Goutte, Kenji Yamada, Éric Gaussier
ISCAS
2008
IEEE
145views Hardware» more  ISCAS 2008»
14 years 1 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
2004
ACM
14 years 27 days ago
GaP: a factor model for discrete data
We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
John F. Canny
CVPR
2001
IEEE
14 years 9 months ago
Learning Representative Local Features for Face Detection
This paper describes a face detection approach via learning local features. The key idea is that local features, being manifested by a collection of pixels in a local region, are ...
Xiangrong Chen, Lie Gu, Stan Z. Li, HongJiang Zhan...
CIKM
2010
Springer
13 years 6 months ago
Yes we can: simplex volume maximization for descriptive web-scale matrix factorization
Matrix factorization methods are among the most common techniques for detecting latent components in data. Popular examples include the Singular Value Decomposition or Nonnegative...
Christian Thurau, Kristian Kersting, Christian Bau...