Shallow Neural Networks' Efficiency in Spherical Polynomial Learning Enhanced by Channel Attention

This research explores improvements in the learning capabilities of shallow neural networks, specifically focusing on the efficient learning of low-degree spherical polynomials. The introduction of learnable channel attention is a key aspect, potentially leading to improved performance in relevant applications.