Bibliography (11):

1. Scaling Laws from the Data Manifold Dimension

2. Scaling Laws for Deep Learning

3. A Solvable Model of Neural Scaling Laws

4. Wikipedia Bibliography:

   1. https://en.wikipedia.org/wiki/Kernel_method  :

      https://en.wikipedia.org/wiki/Kernel_method

   2. MNIST database

   3. https://en.wikipedia.org/wiki/Gaussian_function  :

      https://en.wikipedia.org/wiki/Gaussian_function

   4. https://en.wikipedia.org/wiki/Gaussian_random_field  :

      https://en.wikipedia.org/wiki/Gaussian_random_field

   5. https://en.wikipedia.org/wiki/Kernel_regression  :

      https://en.wikipedia.org/wiki/Kernel_regression

   6. https://en.wikipedia.org/wiki/Kriging  :

      https://en.wikipedia.org/wiki/Kriging

   7. https://en.wikipedia.org/wiki/Eigenvectors  :

      https://en.wikipedia.org/wiki/Eigenvectors

   8. Principal component analysis