Stephen Wright and three colleagues were announced winners of the Test of Time Award at the 2020 Conference on Neural Information Processing Systems (NeurIPS). The award is for the paper judged most influential from NeurIPS 2009, 2010, and 2011.

Wright and his coauthors received the award for their 2011 paper “Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent.” The paper proposed an alternative way to implement Stochastic Gradient Descent (SGD) without any locking of memory access, that “outperforms alternative schemes that use locking by an order of magnitude.” SGD is the algorithm that drives many machine learning systems.

See this [12-minute talk]( by Chris Re about the paper.