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SODA
2001
ACM
147views Algorithms» more  SODA 2001»
15 years 2 months ago
Sublinear time approximate clustering
Clustering is of central importance in a number of disciplines including Machine Learning, Statistics, and Data Mining. This paper has two foci: 1 It describes how existing algori...
Nina Mishra, Daniel Oblinger, Leonard Pitt
115
Voted
ICNC
2005
Springer
15 years 6 months ago
An Incremental Learning Method Based on SVM for Online Sketchy Shape Recognition
This paper presents briefly an incremental learning method based on SVM for online sketchy shape recognition. It can collect all classified results corrected by user and select som...
Zhengxing Sun, Lisha Zhang, Enyi Tang
83
Voted
NAACL
2007
15 years 2 months ago
Tree Revision Learning for Dependency Parsing
We present a revision learning model for improving the accuracy of a dependency parser. The revision stage corrects the output of the base parser by means of revision rules learne...
Giuseppe Attardi, Massimiliano Ciaramita
113
Voted
JASIS
2000
143views more  JASIS 2000»
15 years 18 days ago
Discovering knowledge from noisy databases using genetic programming
s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...
Man Leung Wong, Kwong-Sak Leung, Jack C. Y. Cheng
RSFDGRC
1999
Springer
135views Data Mining» more  RSFDGRC 1999»
15 years 5 months ago
The Iterated Version Space Learning
Inspired with Version Space learning, the Iterated Version Space Algorithm (IVSA) has been designed and implemented to learn disjunctive concepts. IVSA dynamically partitions its s...
Jianna Jian Zhang, Nick Cercone