24 search results - page 3 / 5 » Learning in Gibbsian Fields: How Accurate and How Fast Can I... |
GECCO
2008
Springer
13 years 7 months ago
2008
Springer
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
ICCV
2003
IEEE
14 years 8 months ago
2003
IEEE
Example-based methods are effective for parameter estimation problems when the underlying system is simple or the dimensionality of the input is low. For complex and high-dimensio...
LREC
2008
13 years 7 months ago
2008
The availability of a huge mass of textual data in electronic format has increased the need for fast and accurate techniques for textual data processing. Machine learning and stat...
CASES
2006
ACM
14 years 7 days ago
2006
ACM
Developing an optimizing compiler for a newly proposed architecture is extremely difficult when there is only a simulator of the machine available. Designing such a compiler requ...
JFR
2006
13 years 6 months ago
2006
In mobile robotics, there are often features that, while potentially powerful for improving navigation, prove difficult to profit from as they generalize poorly to novel situations...