230 search results - page 9 / 46 » Sparse matrix factorization on massively parallel computers |
82
Voted
ECCV
2006
Springer
15 years 11 months ago
2006
Springer
Non-negative tensor factorization (NTF) has recently been proposed as sparse and efficient image representation (Welling and Weber, Patt. Rec. Let., 2001). Until now, sparsity of t...
77
Voted
CIKM
2010
Springer
14 years 8 months ago
2010
Springer
Matrix factorization methods are among the most common techniques for detecting latent components in data. Popular examples include the Singular Value Decomposition or Nonnegative...
ICPR
2010
IEEE
15 years 4 months ago
2010
IEEE
In this paper we develop a probabilistic interpretation and a full Bayesian inference for non-negative matrix deconvolution (NMFD) model. Our ultimate goal is unsupervised extract...
IAJIT
2011
14 years 4 months ago
2011
: The present paper discusses the implementations of sparse matrix-vector products, which are crucial for high performance solutions of large-scale linear equations, on a PC-Cluste...
PPOPP
2010
ACM
15 years 6 months ago
2010
ACM
In LAPACK many matrix operations are cast as block algorithms which iteratively process a panel using an unblocked algorithm and then update a remainder matrix using the high perf...