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» Generalization Bounds for Learning Kernels
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ICML
2007
IEEE
14 years 8 months ago
A kernel path algorithm for support vector machines
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky
ALT
2002
Springer
14 years 4 months ago
On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum
Abstract. In this paper we analyze the relationships between the eigenvalues of the m × m Gram matrix K for a kernel k(·, ·) corresponding to a sample x1, . . . , xm drawn from ...
John Shawe-Taylor, Christopher K. I. Williams, Nel...
FOCM
2006
97views more  FOCM 2006»
13 years 7 months ago
Learning Rates of Least-Square Regularized Regression
This paper considers the regularized learning algorithm associated with the leastsquare loss and reproducing kernel Hilbert spaces. The target is the error analysis for the regres...
Qiang Wu, Yiming Ying, Ding-Xuan Zhou
ICML
2006
IEEE
14 years 8 months ago
Generalized spectral bounds for sparse LDA
We present a discrete spectral framework for the sparse or cardinality-constrained solution of a generalized Rayleigh quotient. This NPhard combinatorial optimization problem is c...
Baback Moghaddam, Yair Weiss, Shai Avidan
ICML
2002
IEEE
14 years 8 months ago
Diffusion Kernels on Graphs and Other Discrete Input Spaces
The application of kernel-based learning algorithms has, so far, largely been confined to realvalued data and a few special data types, such as strings. In this paper we propose a...
Risi Imre Kondor, John D. Lafferty