This report documents ideas for improving the field of machine learning, which arose from discussions at the ML Retrospectives workshop at NeurIPS 2019. The goal of the report is to disseminate these ideas more broadly, and in turn encourage continuing discussion about how the field could improve along these axes. We focus on topics that were most discussed at the workshop: incentives for encouraging alternate forms of scholarship, re-structuring the review process, participation from academia and industry, and how we might better train computer scientists as scientists. Videos from the workshop can be accessed at https://slideslive.com/neurips/west-114-115-retrospectives-a-venue-for-selfreflection-in-ml-research
@article{arxiv.2007.10546,
title = {Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop},
author = {Shagun Sodhani and Mayoore S. Jaiswal and Lauren Baker and Koustuv Sinha and Carl Shneider and Peter Henderson and Joel Lehman and Ryan Lowe},
journal= {arXiv preprint arXiv:2007.10546},
year = {2020}
}