3397-3415.
(https://www.di.ens.fr/~mallat/papiers/MallatPursuit93.pdf)

This implementation is based on Rubinstein, R., Zibulevsky, M. and Elad,
M., Efficient Implementation of the K-SVD Algorithm using Batch Orthogonal
Matching Pursuit Technical Report - CS Technion, April 2008.
https://www.cs.technion.ac.il/~ronrubin/Publications/KSVD-OMP-v2.pdf

Examples
--------
>>> from sklearn.datasets import make_regression
>>> from sklearn.linear_model import orthogonal_mp_gram
>>> X, y = make_regression(noise=4, random_state=0)
>>> coef = orthogonal_mp_gram(X.T @ X, X.T @ y)
>>> coef.shape
(100,)
>>> X[:1,] @ coef
array([-78.68...])
r