e468a76212a58c1af94a3d235151944a-Supplemental-Conference.pdf

Reproducibility319 The backbone recommendation model, DLRM by Naumov et al. [2019], has an open-source PyTorch320 implementation available on Github which includes an implementation of CE. For CCE you need a321 fast library for K-means. We recommend the open-sourced implementation by Johnson et al. [2019]322 for better performance, but you can also use the implementation in Scikit-learn [Pedregosa et al.,323 2011]. The baseline result should be straightforward to reproduce as we closely follow the instructions324 provided by Naumov et al. [2019]. For the CE methods, we only need to change two functions in325 the code: create_emband apply_emb. We suggest using a class for each CE method; see Figure 3.326 For the random hash function, one could use a universal hash function or numpy.random.randint.327