MLSys: The New Frontier of Machine Learning Systems

MLSys: The New Frontier of Machine Learning Systems
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MLSys：机器学习系统的新前沿

DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Ameet Talwalkar
Ameet Talwalkar
中科院分区：
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文献类型：
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作者：
Alexander J. Ratner;Dan Alistarh;G. Alonso;D. Andersen;Peter D. Bailis;Sarah Bird;Nicholas Carlini;Bryan Catanzaro;J. Chayes;E. Chung;B. Dally;J. Dean;I. Dhillon;A. Dimakis;P. Dubey;C. Elkan;G. Fursin;G. Ganger;L. Getoor;Phillip B. Gibbons;Garth A. Gibson;Joseph Gonzalez;Justin Emile Gottschlich;Song Han;K. Hazelwood;Furong Huang;Martin Jaggi;Kevin G. Jamieson;Michael I. Jordan;Gauri Joshi;Rania Y. Khalaf;J. Knight;Jakub Konecný;Tim Kraska;Arun Kumar;Anastasios Kyrillidis;Aparna Lakshmiratan;Jing Li;S. Madden;H. B. McMahan;E. Meijer;Ioannis Mitliagkas;R. Monga;D. Murray;K. Olukotun;Dimitris Papailiopoulos;Gennady Pekhimenko;Theodoros Rekatsinas;Afshin Rostamizadeh;Christopher Ré;Christopher De Sa;Hanie Sedghi;S. Sen;Virginia Smith;Alex Smola;D. Song;Evan R. Sparks;I. Stoica;V. Sze;Madeleine Udell;J. Vanschoren;S. Venkataraman;R. Vinayak;Markus Weimer;A. Wilson;E. Xing;M. Zaharia;Ce Zhang;Ameet Talwalkar

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机器学习 (ML) 技术的采用正在迅速增加。然而，在实际部署中设计和实现支持机器学习模型的系统仍然是一个重大障碍，这在很大程度上是由于现代机器学习方法的开发和部署概况截然不同，以及更广泛采用所带来的一系列实际问题。我们建议在传统系统和 ML 社区的交叉点培育一个新的系统机器学习研究社区，重点关注诸如用于 ML 的硬件系统、用于 ML 的软件系统以及针对超出预测准确性的指标进行优化的 ML 等主题。为此，我们描述了一个新的会议 MLSys，该会议明确针对系统和机器学习交叉领域的研究，其计划委员会由系统和机器学习领域的专家平均分配，并明确关注两者交叉领域的主题。
Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains a significant obstacle, in large part due to the radically different development and deployment profile of modern ML methods, and the range of practical concerns that come with broader adoption. We propose to foster a new systems machine learning research community at the intersection of the traditional systems and ML communities, focused on topics such as hardware systems for ML, software systems for ML, and ML optimized for metrics beyond predictive accuracy. To do this, we describe a new conference, MLSys, that explicitly targets research at the intersection of systems and machine learning with a program committee split evenly between experts in systems and ML, and an explicit focus on topics at the intersection of the two.