Deep learning
I've sort of run adjacent to the field of machine learning in the last few years, but haven't really dove in to the existing literature. This seems to be a pretty interesting overview.Out of curiosity, do many implementations of convolutional neural networks take advantage of FFT, DCT, or some other fast orthonormal transform to compute the transition between layers, or are the kernel sizes small enough that there isn't a great advantage to that?