Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n × m matrix M into a product of a nonnegative n × d matrix W and a nonnegative d × m matrix H. NMF has a wide variety of applications, including bioinformatics, chemometrics, communication complexity, machine learning, polyhedral combinatorics, among many others. A longstanding open question, posed by Cohen and Rothblum in 1993, is whether every rational matrix M has an NMF with minimal d whose factors W and H are also rational. We answer this question negatively, by exhibiting a matrix M for which W and H require irrational entries. As an application of this result, we show that state minimization of labeled Markov chains can require the introducti...
An exact nonnegative matrix decomposition algorithm is proposed. This is achieved by 1) Taking a non...
Nonnegative Matrix Factorization (NMF) is a data analysis technique which allows compression and int...
Nonnegative matrix factorization (NMF) has drawn considerable interest in recent years due to its im...
Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n x m matri...
Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n × m matri...
Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n*m matrix ...
Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n × m matri...
In the Nonnegative Matrix Factorization (NMF) problem we are given an n×m nonnegative matrix M and a...
The exact nonnegative matrix factorization (exact NMF) problem is the following: given an m-by-n non...
Nonnegative Matrix Factorization (NMF) is a popular data analysis tool for nonnegative data, able to...
Nonnegative matrix factorization (NMF) consists in finding two nonnegative matrices whose product is...
Nonnegative matrix factorization (NMF) is a data analysis technique based on the approximation of a ...
AbstractAlthough nonnegative matrix factorization (NMF) favors a sparse and part-based representatio...
Nonnegative matrix factorization (NMF) has been success-fully applied to different domains as a tech...
AbstractThe nonnegative rank of a nonnegative matrix is the smallest number of nonnegative rank-one ...
An exact nonnegative matrix decomposition algorithm is proposed. This is achieved by 1) Taking a non...
Nonnegative Matrix Factorization (NMF) is a data analysis technique which allows compression and int...
Nonnegative matrix factorization (NMF) has drawn considerable interest in recent years due to its im...
Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n x m matri...
Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n × m matri...
Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n*m matrix ...
Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n × m matri...
In the Nonnegative Matrix Factorization (NMF) problem we are given an n×m nonnegative matrix M and a...
The exact nonnegative matrix factorization (exact NMF) problem is the following: given an m-by-n non...
Nonnegative Matrix Factorization (NMF) is a popular data analysis tool for nonnegative data, able to...
Nonnegative matrix factorization (NMF) consists in finding two nonnegative matrices whose product is...
Nonnegative matrix factorization (NMF) is a data analysis technique based on the approximation of a ...
AbstractAlthough nonnegative matrix factorization (NMF) favors a sparse and part-based representatio...
Nonnegative matrix factorization (NMF) has been success-fully applied to different domains as a tech...
AbstractThe nonnegative rank of a nonnegative matrix is the smallest number of nonnegative rank-one ...
An exact nonnegative matrix decomposition algorithm is proposed. This is achieved by 1) Taking a non...
Nonnegative Matrix Factorization (NMF) is a data analysis technique which allows compression and int...
Nonnegative matrix factorization (NMF) has drawn considerable interest in recent years due to its im...