Advances in next-generation sequencing technologies have accelerated the momentum of
metagenomic studies, which is increasing yearly. The metagenomics field is one of the …

As reproducibility becomes a greater concern, conferences have largely converged to a
strategy of asking reviewers to indicate whether code was attached to a submission. This …

This article describes how data science techniques—machine learning and natural
language processing—can be used to open the black box of government data. It then …

Subsampling algorithms are a natural approach to reduce data size before fitting models on
massive datasets. In recent years, several works have proposed methods for subsampling …

Leveraging innovations in Machine Learning (ML) research is of great current interest to
researchers across the sciences, including networking research. However, using ML for …

The concern that Artificial Intelligence (AI) and Machine Learning (ML) are entering a"
reproducibility crisis" has spurred significant research in the past few years. Yet with each …

Caliban is a command line tool that helps researchers launch and track their numerical
experiments in an isolated, reproducible computing environment. It was developed by …

Results in machine learning scholarship are sometimes based on untested, difficultto-read
code that has only been seen by a single researcher. We argue that this is bad, and that …