Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop

TL;DR

This paper summarizes discussions from the NeurIPS 2019 Retrospectives Workshop on improving machine learning research practices, including incentives, review processes, and training, aiming to foster ongoing community dialogue.

Contribution

It compiles and disseminates diverse ideas from a major workshop to promote improvements in ML research culture and methodology.

Findings

Discussion on incentives for diverse scholarship

Proposals for restructuring the review process

Emphasis on better training for computer scientists

Abstract

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