512 search results - page 86 / 103 » On Evolutionary Optimization of Large Problems Using Small P... |
EDBT
2010
ACM
13 years 10 months ago
2010
ACM
The specification of schema mappings has proved to be time and resource consuming, and has been recognized as a critical bottleneck to the large scale deployment of data integrati...
APPROX
2008
Springer
13 years 9 months ago
2008
Springer
Clustering is a common problem in the analysis of large data sets. Streaming algorithms, which make a single pass over the data set using small working memory and produce a cluster...
IJIT
2004
13 years 8 months ago
2004
This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear un...
IWANN
1999
Springer
13 years 11 months ago
1999
Springer
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
ISCI
2008
13 years 7 months ago
2008
The use of frequent itemsets has been limited by the high computational cost as well as the large number of resulting itemsets. In many real-world scenarios, however, it is often ...