Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks - RCR Report

This is the Replicated Computational Results (RCR) Report for our TOSEM paper ”Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks”, where we propose a novel client-server architecture allowing to leverage the high accuracy of huge neural networks running on remote servers while reducing the economical and latency costs typically coming from using such models. As part of this RCR, we provide a replication package, which allows the full replication of all our results and is specifically designed to facilitate reuse.