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» Dynamically Adapting Kernels in Support Vector Machines
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TKDE
2010
168views more  TKDE 2010»
13 years 8 months ago
Completely Lazy Learning
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, San...
CVPR
2008
IEEE
14 years 11 months ago
Margin-based discriminant dimensionality reduction for visual recognition
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
Hakan Cevikalp, Bill Triggs, Frédéri...
ICSE
2009
IEEE-ACM
14 years 4 months ago
Toward deeply adaptive societies of digital systems
Modern societies are pervaded by computerized, heterogeneous devices designed for specific purposes, but also more and more often capable of interacting with other devices for en...
Antonio Carzaniga, Giovanni Denaro, Mauro Pezz&egr...
SOFSEM
2007
Springer
14 years 3 months ago
Spatial Selection of Sparse Pivots for Similarity Search in Metric Spaces
Similarity search is a fundamental operation for applications that deal with unstructured data sources. In this paper we propose a new pivot-based method for similarity search, ca...
Oscar Pedreira, Nieves R. Brisaboa
JMM2
2006
111views more  JMM2 2006»
13 years 9 months ago
A Microscopic Telepathology System for Multiresolution Computer-Aided Diagnostics
The aim of the presented system is simplification and speedup of the daily pathological examination routine. The system combines telepathology with computer-aided diagnostics algor...
Grigory Begelman, Michael Pechuk, Ehud Rivlin, Edm...