2512 search results - page 133 / 503 » Learning from Highly Structured Data by Decomposition |
CIVR
2008
Springer
14 years 12 months ago
2008
Springer
In information retrieval, sub-space techniques are usually used to reveal the latent semantic structure of a data-set by projecting it to a low dimensional space. Non-negative mat...
HPDC
1999
IEEE
15 years 2 months ago
1999
IEEE
Efficient and robust metacomputing requires the decomposition of complex jobs into tasks that must be scheduled on distributed processing nodes. There are various ways of creating...
108
click to vote
GCB
2007
Springer
15 years 4 months ago
2007
Springer
: The recent availability of large data sets of protein- protein-interactions (PPIs) from various species offers new opportunities for functional genomics and proteomics. We descri...
100
click to vote
UAI
2008
14 years 11 months ago
2008
Identifying co-varying causal elements in very high dimensional feature space with internal structures, e.g., a space with as many as millions of linearly ordered features, as one...
115
click to vote
BMCBI
2006
14 years 10 months ago
2006
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...