5463 search results - page 49 / 1093 » Evaluating algorithms that learn from data streams |
215
Voted
ICDE
2008
IEEE
16 years 1 months ago
2008
IEEE
The overwhelming flow of information in many data stream applications forces many companies to outsource to a third-party the deployment of a Data Stream Management System (DSMS) f...
106
Voted
PODS
2006
ACM
16 years 19 days ago
2006
ACM
We study the randomized version of a computation model (introduced in [9, 10]) that restricts random access to external memory and internal memory space. Essentially, this model c...
101
Voted
SIGMOD
2004
ACM
16 years 20 days ago
2004
ACM
Many algorithms have been proposed to approximate holistic aggregates, such as quantiles and heavy hitters, over data streams. However, little work has been done to explore what t...
122
Voted
MIR
2005
ACM
15 years 6 months ago
2005
ACM
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
105
Voted
ICIP
2009
IEEE
14 years 10 months ago
2009
IEEE
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...