Computer Systems Have 99 Problems, Let's Not Make Machine Learning Another One

David A. Mohaisen, Songqing Chen
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Abstract

Machine learning techniques are finding many applications in computer systems, including many tasks that require decision making: network optimization, quality of service assurance, and security. We believe machine learning systems are here to stay, and to materialize on their potential we advocate a fresh look at various key issues that need further attention, including security as a requirement and system complexity, and how machine learning systems affect them. We also discuss reproducibility as a key requirement for sustainable machine learning systems, and leads to pursuing it.
计算机系统有99个问题,我们不要让机器学习成为另一个问题
机器学习技术在计算机系统中有许多应用,包括许多需要决策的任务:网络优化、服务质量保证和安全。我们相信机器学习系统将继续存在,并且为了实现其潜力,我们主张重新审视需要进一步关注的各种关键问题,包括安全性作为要求和系统复杂性,以及机器学习系统如何影响它们。我们还讨论了可重复性作为可持续机器学习系统的关键要求,并导致追求它。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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