@article {5557, title = {For HyperBFs AGOP is a greedy approximation to gradient descent}, number = {148}, year = {2024}, month = {07/2024}, abstract = {

The Average Gradient Outer Product (AGOP) provides a novel approach to feature learning in neural networks. We applied both AGOP and Gradient Descent to learn the matrix M in the Hyper Basis Function Network (HyperBF) and observed very similar performance. We show formally that AGOP is a greedy approximation of gradient descent.

}, author = {Yulu Gan and Tomaso Poggio} }