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» Support Vector Machines: Theory and Applications
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ICML
2008
IEEE
16 years 19 days ago
Training SVM with indefinite kernels
Similarity matrices generated from many applications may not be positive semidefinite, and hence can't fit into the kernel machine framework. In this paper, we study the prob...
Jianhui Chen, Jieping Ye
FLAIRS
2008
15 years 2 months ago
On Using SVM and Kolmogorov Complexity for Spam Filtering
As a side effect of e-marketing strategy the number of spam e-mails is rocketing, the time and cost needed to deal with spam as well. Spam filtering is one of the most difficult t...
Sihem Belabbes, Gilles Richard
NECO
2000
190views more  NECO 2000»
14 years 11 months ago
Generalized Discriminant Analysis Using a Kernel Approach
We present a new method that we call Generalized Discriminant Analysis (GDA) to deal with nonlinear discriminant analysis using kernel function operator. The underlying theory is ...
G. Baudat, Fatiha Anouar
SAC
2006
ACM
15 years 5 months ago
Privacy-preserving SVM using nonlinear kernels on horizontally partitioned data
Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security co...
Hwanjo Yu, Xiaoqian Jiang, Jaideep Vaidya
MICRO
2005
IEEE
130views Hardware» more  MICRO 2005»
15 years 5 months ago
Exploiting Vector Parallelism in Software Pipelined Loops
An emerging trend in processor design is the addition of short vector instructions to general-purpose and embedded ISAs. Frequently, these extensions are employed using traditiona...
Samuel Larsen, Rodric M. Rabbah, Saman P. Amarasin...