TrIK-SVM : an alternative decomposition for kernel methods in Krein spaces

Abstract : The proposed work aims at proposing a alternative kernel decomposition in the context of kernel machines with indefinite kernels. The original paper of KSVM (SVM in Kre˘ ın spaces) uses the eigen-decomposition, our proposition avoids this decompostion. We explain how it can help in designing an algorithm that won't require to compute the full kernel matrix. Finally we illustrate the good behavior of the proposed method compared to KSVM.
Document type :
Conference papers
Complete list of metadatas

Cited literature [12 references]  Display  Hide  Download

https://hal-clermont-univ.archives-ouvertes.fr/hal-02049004
Contributor : Gaelle Loosli <>
Submitted on : Tuesday, February 26, 2019 - 9:09:08 AM
Last modification on : Thursday, February 28, 2019 - 1:20:18 AM
Long-term archiving on : Monday, May 27, 2019 - 1:03:58 PM

Files

trikSVMreduced.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02049004, version 1
  • ARXIV : 1902.10569

Citation

Gaëlle Loosli. TrIK-SVM : an alternative decomposition for kernel methods in Krein spaces. ESANN - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 2019, Bruges, Belgium. ⟨hal-02049004⟩

Share

Metrics

Record views

34

Files downloads

21