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SSPR
2010
Springer
13 years 6 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
DMIN
2008
190views Data Mining» more  DMIN 2008»
13 years 10 months ago
Optimization of Self-Organizing Maps Ensemble in Prediction
The knowledge discovery process encounters the difficulties to analyze large amount of data. Indeed, some theoretical problems related to high dimensional spaces then appear and de...
Elie Prudhomme, Stéphane Lallich
BIBE
2009
IEEE
131views Bioinformatics» more  BIBE 2009»
13 years 11 months ago
Learning Scaling Coefficient in Possibilistic Latent Variable Algorithm from Complex Diagnosis Data
—The Possibilistic Latent Variable (PLV) clustering algorithm is a powerful tool for the analysis of complex datasets due to its robustness toward data distributions of different...
Zong-Xian Yin
JBI
2006
107views Bioinformatics» more  JBI 2006»
13 years 8 months ago
KDE Bioscience: Platform for bioinformatics analysis workflows
Bioinformatics is a dynamic research area in which a large number of algorithms and programs have been developed rapidly and independently without much consideration so far of the...
Qiang Lu, Pei Hao, Vasa Curcin, Wei-Zhong He, Yuan...
ESANN
2004
13 years 9 months ago
Neural methods for non-standard data
Standard pattern recognition provides effective and noise-tolerant tools for machine learning tasks; however, most approaches only deal with real vectors of a finite and fixed dime...
Barbara Hammer, Brijnesh J. Jain