Kernels …
Klaus- ̈ller Lecture at TUB 2021
Digestion: Use of kernels
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[SSM et al. 98]
[SSM et al. 98]
[Mika et al. 02] [Zien et al. 00, Tsuda et al. 02, Sonnenburg et al. 05]
Kernels for graphs, trees, strings etc.
Klaus- ̈ller Lecture at TUB 2021
Remark: Kernelizing linear algorithms
Klaus- ̈ller Lecture at TUB 2021
Klaus- ̈ller Lecture at TUB 2021
Implementation Issues: working set methods
Klaus- ̈ller Lecture at TUB 2021
Implementation Issues: working set methods II
Klaus- ̈ller Lecture at TUB 2021
Klaus- ̈ller Lecture at TUB 2021
SMO continued
Klaus- ̈ller Lecture at TUB 2021
Klaus- ̈ller Lecture at TUB 2021
SVMs for Regression
Klaus- ̈ller Lecture at TUB 2021
SVMs for Regression II
Klaus- ̈ller Lecture at TUB 2021
Remark: Kernelizing linear algorithms
Klaus- ̈ller Lecture at TUB 2021
Kernel PCA
[cf. Schölkopf, Smola, Müller 98]
Klaus- ̈ller Lecture at TUB 2021
PCA in high dimensional feature spaces
Nonlinear PCA as an Eigenvalue problem
Klaus- ̈ller Lecture at TUB 2021
Feature Extraction
Centering in Feature Space
Klaus- ̈ller Lecture at TUB 2021
Example: 8 kPCA components with RBF kernel
Klaus- ̈ller Lecture at TUB 2021
Klaus- ̈ller Lecture at TUB 2021
Denoising II
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