Optimal Symmetries in Binary Classification.

arXiv:2408.08823v2 Announce Type: replace-cross Abstract: We develop a theoretical foundation for designing group-equivariant neural networks that align the choice of symmetries with the underlying probability distributions of the data. Utilising the general s