Russell Zaretzki

TL;DR: This paper addresses the problem of learning over-complete dictionaries for the coupled feature spaces, where the learned dictionaries also reflect the relationship between the two spaces, and proposes a Bayesian method using a beta process prior to learn the over- complete dictionaries.

TL;DR: A very large and frequently updated collection of version control data for FLOSS projects named World of Code (WoC), which is capable of supporting trend evaluation, ecosystem measurement, and the determination of package usage, and is expected to spur investigation into global properties of OSS development leading to increased resiliency of the entire OSS ecosystem.

TL;DR: In this article, the authors provide evidence that two particular types of enabling institutions, countries' property rights regulations and cooperative actions, are useful for lowering the obstacles presented by informal activity.

TL;DR: Through a comprehensive evaluation of the modeling results, the authors find that the ZIOP model performs well relative to the traditional ordered probit (OP) model, and can serve as an alternative in future studies of crash injury severity.

TL;DR: The Skill Plot is introduced, a method that it is directly relevant to a decision maker who must use a diagnostic test and shows that the skill‐based cutoff inferred from the plot is equivalent to the cutoff indicated by optimizing the posterior odds in accordance with Bayesian decision theory.