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PR
2006
93views more  PR 2006»
14 years 9 months ago
Learning the kernel parameters in kernel minimum distance classifier
Choosing appropriate values for kernel parameters is one of the key problems in many kernel-based methods because the values of these parameters have significant impact on the per...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
CVPR
2003
IEEE
15 years 11 months ago
Mean-shift Blob Tracking through Scale Space
The mean-shift algorithm is an efficient technique for tracking 2D blobs through an image. Although the scale of the mean-shift kernel is a crucial parameter, there is presently n...
Robert T. Collins
ICANN
2007
Springer
15 years 3 months ago
Some Properties of the Gaussian Kernel for One Class Learning
This paper proposes a novel approach for directly tuning the gaussian kernel matrix for one class learning. The popular gaussian kernel includes a free parameter, σ, that requires...
Paul F. Evangelista, Mark J. Embrechts, Boleslaw K...
104
Voted
PVLDB
2010
114views more  PVLDB 2010»
14 years 8 months ago
Peer coordination through distributed triggers
This is a demonstration of data coordination in a peer data management system through the employment of distributed triggers. The latter express in a declarative manner individual...
Verena Kantere, Maher Manoubi, Iluju Kiringa, Timo...
114
Voted
KES
2007
Springer
15 years 3 months ago
Inductive Concept Retrieval and Query Answering with Semantic Knowledge Bases Through Kernel Methods
This work deals with the application of kernel methods to structured relational settings such as semantic knowledge bases expressed in Description Logics. Our method integrates a n...
Nicola Fanizzi, Claudia d'Amato