Unsupervised MKL in Multi-layer Kernel Machines [article]

Akhil Meethal and Asharaf S and Sumitra S
2021 arXiv   pre-print
Kernel based Deep Learning using multi-layer kernel machines(MKMs) was proposed by Y.Cho and L.K. Saul in . In MKMs they used only one kernel(arc-cosine kernel) at a layer for the kernel PCA-based feature extraction. We propose to use multiple kernels in each layer by taking a convex combination of many kernels following an unsupervised learning strategy. Empirical study is conducted on mnist-back-rand, mnist-back-image and mnist-rot-back-image datasets generated by adding random noise in the
more » ... age background of MNIST dataset. Experimental results indicate that using MKL in MKMs earns a better representation of the raw data and improves the classifier performance.
arXiv:2111.13769v1 fatcat:ahmpywdwqfc6bbl4pyjyfn5e3y