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Justin Gottschlich

2 accepted papers

2019

A Zero-Positive Learning Approach for Diagnosing Software Performance Regressions

NeurIPS 2019poster

The field of machine programming (MP), the automation of the development of software, is making notable research advances. This is, in part, due to the emergence of a wide range of novel techniques in machine learning. In this paper, we apply MP to the automation of software performance regression t…

2018

Precision and Recall for Time Series

NeurIPS 2018spotlight

Classical anomaly detection is principally concerned with point-based anomalies, those anomalies that occur at a single point in time. Yet, many real-world anomalies are range-based, meaning they occur over a period of time. Motivated by this observation, we present a new mathematical model to evalu…