Sciweavers

ICA
2010
Springer
13 years 8 months ago
Using Non-Negative Matrix Factorization for Removing Show-Through
Scanning process usually degrades digital documents due to the contents of the backside of the scanned manuscript. This is often because of the show-through effect, i.e. the backsi...
Farnood Merrikh-Bayat, Massoud Babaie-Zadeh, Chris...
JMLR
2010
195views more  JMLR 2010»
13 years 10 months ago
Online Learning for Matrix Factorization and Sparse Coding
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
JMLR
2008
188views more  JMLR 2008»
13 years 11 months ago
Maximal Causes for Non-linear Component Extraction
We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
Jörg Lücke, Maneesh Sahani
CORR
2002
Springer
180views Education» more  CORR 2002»
13 years 11 months ago
Non-negative sparse coding
Abstract. Non-negative sparse coding is a method for decomposing multivariate data into non-negative sparse components. In this paper we briefly describe the motivation behind this...
Patrik O. Hoyer
CORR
2004
Springer
152views Education» more  CORR 2004»
13 years 11 months ago
Non-negative matrix factorization with sparseness constraints
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been a...
Patrik O. Hoyer
CSDA
2008
128views more  CSDA 2008»
13 years 11 months ago
On the equivalence between Non-negative Matrix Factorization and Probabilistic Latent Semantic Indexing
Non-negative Matrix Factorization (NMF) and Probabilistic Latent Semantic Indexing (PLSI) have been successfully applied to document clustering recently. In this paper, we show th...
Chris H. Q. Ding, Tao Li, Wei Peng
CORR
2008
Springer
126views Education» more  CORR 2008»
13 years 11 months ago
Non-Negative Matrix Factorization, Convexity and Isometry
Traditional Non-Negative Matrix Factorization (NMF) [19] is a successful algorithm for decomposing datasets into basis function that have reasonable interpretation. One problem of...
Nikolaos Vasiloglou, Alexander G. Gray, David V. A...
CORR
2008
Springer
113views Education» more  CORR 2008»
13 years 11 months ago
Clustering of scientific citations in Wikipedia
The instances of templates in Wikipedia form an interesting data set of structured information. Here I focus on the cite journal template that is primarily used for citation to art...
Finn Årup Nielsen
ICASSP
2010
IEEE
13 years 11 months ago
Noise-to-mask ratio minimization by weighted non-negative matrix factorization
This paper proposes a novel algorithm for minimizing the perceptual distortion in non-negative matrix factorization (NMF) based audio representation. We formulate the noise-to-mas...
Joonas Nikunen, Tuomas Virtanen
ICASSP
2010
IEEE
13 years 11 months ago
NMF with time-frequency activations to model non stationary audio events
Real world sounds often exhibit non-stationary spectral characteristics such as those produced by a harpsichord or a guitar. The classical Non-negative Matrix Factorization (NMF) ...
Romain Hennequin, Roland Badeau, Bertrand David