191 search results - page 16 / 39 » Data Condensation in Large Databases by Incremental Learning... |
EDBT
2009
ACM
14 years 6 days ago
2009
ACM
Structured data including sets, sequences, trees and graphs, pose significant challenges to fundamental aspects of data management such as efficient storage, indexing, and simila...
ICDE
2003
IEEE
14 years 9 months ago
2003
IEEE
Clustering of large data bases is an important research area with a large variety of applications in the data base context. Missing in most of the research efforts are means for g...
KDD
2006
ACM
14 years 8 months ago
2006
ACM
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
SIGMOD
2007
ACM
14 years 7 months ago
2007
ACM
Map-Reduce is a programming model that enables easy development of scalable parallel applications to process vast amounts of data on large clusters of commodity machines. Through ...
NIPS
2001
13 years 9 months ago
2001
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...