Abstract
One of the key concepts in machine learning is the feature space, which is often referred to as the latent space. A feature space is usually a higher or lower-dimensional space than the original one where the input data lie (which is often referred to as the ambient space).
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Ye, J.C. (2022). Reproducing Kernel Hilbert Space, Representer Theorem. In: Geometry of Deep Learning. Mathematics in Industry, vol 37. Springer, Singapore. https://doi.org/10.1007/978-981-16-6046-7_4
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DOI: https://doi.org/10.1007/978-981-16-6046-7_4
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