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» Recent advancements of fuzzy sets: Theory and practice
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KDD
2004
ACM
211views Data Mining» more  KDD 2004»
15 years 9 months ago
Towards parameter-free data mining
Most data mining algorithms require the setting of many input parameters. Two main dangers of working with parameter-laden algorithms are the following. First, incorrect settings ...
Eamonn J. Keogh, Stefano Lonardi, Chotirat (Ann) R...
CVPR
2006
IEEE
15 years 11 months ago
Applying Ensembles of Multilinear Classifiers in the Frequency Domain
Ensemble methods such as bootstrap, bagging or boosting have had a considerable impact on recent developments in machine learning, pattern recognition and computer vision. Theoret...
Christian Bauckhage, Thomas Käster, John K. T...
KDD
2009
ACM
239views Data Mining» more  KDD 2009»
15 years 10 months ago
Applying syntactic similarity algorithms for enterprise information management
: ? Applying Syntactic Similarity Algorithms for Enterprise Information Management Ludmila Cherkasova, Kave Eshghi, Charles B. Morrey III, Joseph Tucek, Alistair Veitch HP Laborato...
Ludmila Cherkasova, Kave Eshghi, Charles B. Morrey...
KDD
2006
ACM
128views Data Mining» more  KDD 2006»
15 years 9 months ago
On privacy preservation against adversarial data mining
Privacy preserving data processing has become an important topic recently because of advances in hardware technology which have lead to widespread proliferation of demographic and...
Charu C. Aggarwal, Jian Pei, Bo Zhang 0002
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
15 years 3 months ago
SDR: a better trigger for adaptive variance scaling in normal EDAs
Recently, advances have been made in continuous, normal– distribution–based Estimation–of–Distribution Algorithms (EDAs) by scaling the variance up from the maximum–like...
Peter A. N. Bosman, Jörn Grahl, Franz Rothlau...