谷歌维齐尔:一种黑匣子优化服务Google Vizier: A Service for BlackBox Optimization |
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课程网址: | http://videolectures.net/kdd2017_golovin_google_vizier/ |
主讲教师: | Daniel Golovin |
开课单位: | 谷歌、股份有限公司的研究 |
开课时间: | 2017-10-09 |
课程语种: | 英语 |
中文简介: | 任何一个足够复杂的系统,当它变得更容易实验而不是理解时,都会充当一个黑匣子。因此,随着系统变得越来越复杂,黑盒优化变得越来越重要。在本文中,我们描述了谷歌维齐尔,这是一种用于执行黑匣子优化的谷歌内部服务,已成为谷歌事实上的参数调整引擎。谷歌维齐尔用于优化我们的许多机器学习模型和其他系统,并为谷歌的云机器学习HyperTune子系统提供核心功能。我们讨论了我们的需求、基础设施设计、底层算法以及该服务提供的高级功能,如迁移学习和自动提前停止。 |
课程简介: | Any sufficiently complex system acts as a black box when it becomes easier to experiment with than to understand. Hence, black-box optimization has become increasingly important as systems have become more complex. In this paper we describe Google Vizier, a Google-internal service for performing black-box optimization that has become the de facto parameter tuning engine at Google. Google Vizier is used to optimize many of our machine learning models and other systems, and also provides core capabilities to Google's Cloud Machine Learning HyperTune subsystem. We discuss our requirements, infrastructure design, underlying algorithms, and advanced features such as transfer learning and automated early stopping that the service provides. |
关 键 词: | 黑盒优化; 内部服务; 调整参数 |
课程来源: | 视频讲座网 |
数据采集: | 2023-06-07:chenxin01 |
最后编审: | 2023-06-07:chenxin01 |
阅读次数: | 70 |