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» Learning large margin classifiers locally and globally
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SASO
2009
IEEE
14 years 2 months ago
Self-organized Fault-tolerant Routing in Peer-to-Peer Overlays
—In sufficiently large heterogeneous overlays message loss and delays are likely to occur. This has a significant impact on overlay routing, especially on longer paths. The exi...
Wojciech Galuba, Karl Aberer, Zoran Despotovic, Wo...
WWW
2003
ACM
14 years 8 months ago
The chatty web: emergent semantics through gossiping
This paper describes a novel approach for obtaining semantic interoperability among data sources in a bottom-up, semiautomatic manner without relying on pre-existing, global seman...
Karl Aberer, Manfred Hauswirth, Philippe Cudr&eacu...
ACCV
2010
Springer
13 years 2 months ago
Descriptor Learning Based on Fisher Separation Criterion for Texture Classification
Abstract. This paper proposes a novel method to deal with the representation issue in texture classification. A learning framework of image descriptor is designed based on the Fish...
Yimo Guo, Guoying Zhao, Matti Pietikäinen, Zh...
SAC
2006
ACM
14 years 1 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
ICDCS
2002
IEEE
14 years 19 days ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...