A quantization method for neural networks based on quantiles in empirical distributions.
A final project for Harvard's CS 242, "Computing at Scale," taught by Prof. HT Kung.
I collaborated with Ralph Estanboulieh and Ryan Kim on this project. My main contributions involve a significant portion of the code for application of quantization to neural networks, as well a large share of the paper.