Name
Abstract | ||
|---|---|---|
In this paper, dimensionality reduction via matrix factorization with nonnegativity constraints is studied. Because of these constraints, it stands apart from other linear dimensionality reduction methods. Here we explore nonnegative matrix factorization in combination with a classifier for protein fold recognition. Since typically matrix factorization is iteratively done, convergence can be slow. To alleviate this problem, a significantly faster (more than 11 times) algorithm is proposed. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11564096_67 | ECML |
Keywords | Field | DocType |
nonnegativity constraint,linear dimensionality reduction method,matrix factorization,nonnegative matrix factorization,non-negative dimensionality reduction,dimensionality reduction | Convergence (routing),Discrete mathematics,Combinatorics,Dimensionality reduction,Matrix decomposition,Threading (protein sequence),Algorithm,Non-negative matrix factorization,Classifier (linguistics),Mathematics,Constrained optimization | Conference |
Volume | ISSN | ISBN |
3720 | 0302-9743 | 3-540-29243-8 |
Citations | PageRank | References |
2 | 0.42 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Oleg Okun | 1 | 308 | 28.56 |
| Helen Priisalu | 2 | 58 | 4.13 |
| Alexessander Alves | 3 | 6 | 1.92 |