9 search results - page 1 / 2 » The SPARAMAT Approach to Automatic Comprehension of Sparse M... |
IWPC
1999
IEEE
13 years 9 months ago
1999
IEEE
Automatic program comprehension is particularly useful when applied to sparse matrix codes, since it allows to abstract e.g. from specific sparse matrix storage formats used in th...
ICPR
2010
IEEE
13 years 12 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...
ICCV
2003
IEEE
14 years 6 months ago
2003
IEEE
The problem of selecting a subset of relevant features in a potentially overwhelming quantity of data is classic and found in many branches of science. Examples in computer vision...
TSP
2010
12 years 11 months ago
2010
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
CORR
2012
Springer
12 years 20 days ago
2012
Springer
Graphs are fundamental data structures and have been employed for centuries to model real-world systems and phenomena. Random walk with restart (RWR) provides a good proximity sco...