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» On the generalization of soft margin algorithms
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TCS
2010
13 years 7 months ago
Maximal width learning of binary functions
This paper concerns learning binary-valued functions defined on IR, and investigates how a particular type of ‘regularity’ of hypotheses can be used to obtain better generali...
Martin Anthony, Joel Ratsaby
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
14 years 22 days ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 8 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin
CIKM
2009
Springer
14 years 3 months ago
Maximal metric margin partitioning for similarity search indexes
We propose a partitioning scheme for similarity search indexes that is called Maximal Metric Margin Partitioning (MMMP). MMMP divides the data on the basis of its distribution pat...
Hisashi Kurasawa, Daiji Fukagawa, Atsuhiro Takasu,...
BIOID
2008
157views Biometrics» more  BIOID 2008»
13 years 11 months ago
Modeling Marginal Distributions of Gabor Coefficients: Application to Biometric Template Reduction
Abstract. Gabor filters have demonstrated their effectiveness in automatic face recognition. However, one drawback of Gabor-based face representations is the huge amount of data th...
Daniel González-Jiménez, José...