Most implementations of stochastic gradient descent (SGD) rely on floating points. Is there implementations using infinite or finite precision integer arithmetics ?
see eg Neural network training with constrained integer weights Plagianakos, V.P.; Vrahatis, M.N.;
An Integer Recurrent Artificial Neural Network for Classifying Feature Vectors Roelof K Brouwer PEng, Ph
the general idea in various implementations is to represent/approximate real numbers $x \in[0..1]$ as integers in the form $x \cdot 10^m$ where $m$ is some integer exponent.