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» Evaluating algorithms that learn from data streams
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MCS
2005
Springer
16 years 7 hour ago
Ensemble of SVMs for Incremental Learning
Support Vector Machines (SVMs) have been successfully applied to solve a large number of classification and regression problems. However, SVMs suffer from the catastrophic forgetti...
Zeki Erdem, Robi Polikar, Fikret S. Gürgen, N...
MCS
2004
Springer
15 years 12 months ago
Learn++.MT: A New Approach to Incremental Learning
An ensemble of classifiers based algorithm, Learn++, was recently introduced that is capable of incrementally learning new information from datasets that consecutively become avail...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar
ICPR
2006
IEEE
16 years 7 months ago
Learning Pairwise Similarity for Data Clustering
Each clustering algorithm induces a similarity between given data points, according to the underlying clustering criteria. Given the large number of available clustering technique...
Ana L. N. Fred, Anil K. Jain
IDA
2002
Springer
15 years 6 months ago
Evolutionary model selection in unsupervised learning
Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
YongSeog Kim, W. Nick Street, Filippo Menczer
DOA
2001
137views more  DOA 2001»
15 years 8 months ago
Supporting Distributed Processing of Time-Based Media Streams
There are many challenges in devising solutions for online content processing of live networked multimedia sessions. These include content analysis under uncertainty (evidence of ...
Viktor S. Wold Eide, Frank Eliassen, Olav Lysne