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» Evaluating algorithms that learn from data streams
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GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
16 years 19 days ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec
ICDM
2006
IEEE
108views Data Mining» more  ICDM 2006»
16 years 15 days ago
Integrating Features from Different Sources for Music Information Retrieval
Efficient and intelligent music information retrieval is a very important topic of the 21st century. With the ultimate goal of building personal music information retrieval syste...
Tao Li, Mitsunori Ogihara, Shenghuo Zhu
IJON
2006
99views more  IJON 2006»
15 years 6 months ago
Learning vector quantization: The dynamics of winner-takes-all algorithms
Winner-Takes-All (WTA) prescriptions for Learning Vector Quantization (LVQ) are studied in the framework of a model situation: Two competing prototype vectors are updated accordin...
Michael Biehl, Anarta Ghosh, Barbara Hammer
KDD
2005
ACM
124views Data Mining» more  KDD 2005»
16 years 6 months ago
A multinomial clustering model for fast simulation of computer architecture designs
Computer architects utilize simulation tools to evaluate the merits of a new design feature. The time needed to adequately evaluate the tradeoffs associated with adding any new fe...
Kaushal Sanghai, Ting Su, Jennifer G. Dy, David R....
BMCBI
2006
201views more  BMCBI 2006»
15 years 6 months ago
Gene selection algorithms for microarray data based on least squares support vector machine
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao