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ICASSP
2008
IEEE
15 years 4 months ago
Learning the kernel via convex optimization
The performance of a kernel-based learning algorithm depends very much on the choice of the kernel. Recently, much attention has been paid to the problem of learning the kernel it...
Seung-Jean Kim, Argyrios Zymnis, Alessandro Magnan...
ICML
2002
IEEE
15 years 10 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
JMLR
2010
155views more  JMLR 2010»
14 years 8 months ago
Approximate Tree Kernels
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
ICMLC
2010
Springer
14 years 8 months ago
Multiple kernel learning and feature space denoising
We review a multiple kernel learning (MKL) technique called p regularised multiple kernel Fisher discriminant analysis (MK-FDA), and investigate the effect of feature space denois...
Fei Yan, Josef Kittler, Krystian Mikolajczyk
NIPS
2008
14 years 11 months ago
Learning with Consistency between Inductive Functions and Kernels
Regularized Least Squares (RLS) algorithms have the ability to avoid over-fitting problems and to express solutions as kernel expansions. However, we observe that the current RLS ...
Haixuan Yang, Irwin King, Michael R. Lyu