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» Optimizing kernel parameters by second-order methods
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ICASSP
2011
IEEE
12 years 11 months ago
Speaker recognition using multiple kernel learning based on conditional entropy minimization
We applied a multiple kernel learning (MKL) method based on information-theoretic optimization to speaker recognition. Most of the kernel methods applied to speaker recognition sy...
Tetsuji Ogawa, Hideitsu Hino, Nima Reyhani, Noboru...
PAMI
2011
13 years 2 months ago
Kernel Optimization in Discriminant Analysis
— Kernel mapping is one of the most used approaches to intrinsically derive nonlinear classifiers. The idea is to use a kernel function which maps the original nonlinearly separ...
Di You, Onur C. Hamsici, Aleix M. Martínez
ICML
2004
IEEE
14 years 8 months ago
A fast iterative algorithm for fisher discriminant using heterogeneous kernels
We propose a fast iterative classification algorithm for Kernel Fisher Discriminant (KFD) using heterogeneous kernel models. In contrast with the standard KFD that requires the us...
Glenn Fung, Murat Dundar, Jinbo Bi, R. Bharat Rao
KDD
2004
ACM
181views Data Mining» more  KDD 2004»
14 years 8 months ago
Column-generation boosting methods for mixture of kernels
We devise a boosting approach to classification and regression based on column generation using a mixture of kernels. Traditional kernel methods construct models based on a single...
Jinbo Bi, Tong Zhang, Kristin P. Bennett
MP
2008
91views more  MP 2008»
13 years 7 months ago
The rate of convergence of the augmented Lagrangian method for nonlinear semidefinite programming
We analyze the rate of local convergence of the augmented Lagrangian method for nonlinear semidefinite optimization. The presence of the positive semidefinite cone constraint requ...
Defeng Sun, Jie Sun, Liwei Zhang