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๐Ÿ“šTheoryAdvanced

Feature Learning vs Kernel Regime

The kernel (lazy) regime keeps neural network parameters close to their initialization, making training equivalent to kernel regression with a fixed kernel such as the Neural Tangent Kernel (NTK).

#neural tangent kernel#kernel ridge regression#lazy training+12
๐Ÿ“šTheoryAdvanced

Neural Tangent Kernel (NTK)

Neural Tangent Kernel (NTK) describes how wide neural networks train like kernel machines, turning gradient descent into kernel regression in the infinite-width limit.

Advanced
Filtering by:
#gram matrix
#neural tangent kernel
#ntk
#nngp
+12
๐Ÿ“šTheoryAdvanced

Reproducing Kernel Hilbert Spaces (RKHS)

An RKHS is a space of functions where evaluating a function at a point equals taking an inner product with a kernel section, which enables the โ€œkernel trick.โ€

#rkhs#kernel trick#gram matrix+12