Oct 20, 2023 · We propose the use of reproducing kernel Krein space (RKKS) based methods, which require only kernels that admit a positive decomposition.
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Jul 30, 2024 · Conclusion. This paper introduces an alternative to classical kernel methods based on the concept of reproducing kernel Krein spaces (RKKS).
Oct 24, 2023 · Geometric Learning with Positively Decomposable Kernels. (arXiv:2310.13821v1 [cs.LG]) https://ift.tt/JEsTjpz · 2:59 AM · Oct 24, 2023.
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We show that invariant kernels admit a positive decomposition on homogeneous spaces under tractable regularity assumptions. This makes them much easier to ...
Kernel methods are powerful tools in machine learning. Classical kernel methods are based on positive-definite kernels, which map data spaces into ...
[2024] Geometric learning with positively decomposable kernels. To appear in the Journal of Machine Learning Research. Paper Ortega, J.-P. and Yin, D. [2024] ...
Classical kernel methods are based on positive-definite kernels, which map data spaces into reproducing kernel Hilbert spaces (RKHS). Paper · Add Code ...
Co-authors ; Geometric Learning with Positively Decomposable Kernels. N Da Costa, C Mostajeran, JP Ortega, S Said. arXiv preprint arXiv:2310.13821, 2023. 2023 ...
Jun 16, 2021 · This is because √K2 is not the matrix whose entries are the square root of those of K2, but the matrix such that (√K2)2=K2.
Berlin Chen, Cyrus Mostajeran, Salem Said, "Geometric learning of ... Geometric learning with positively decomposable kernels" (2023). Page updated.