Overall complexity for inference with the SGNN++ model depends on the projection layer, O(n • T • d) where n is the observed feature size (*not* overall vocabulary size) which is linear in input size, d is the number of LSH bits specified for each projection vector P j , and T is the number of projection functions used.
it is easy to customize our model for different devices such as watches, phones or ioT with different size constraints.