综合资源展示 综合资源展示

最小化 最大化
«返回

An adaptive control momentum method as an optimizer in the cloud

  • 详细信息
标题: An adaptive control momentum method as an optimizer in the cloud
资源摘要: Publication date: December 2018
Source:Future Generation Computer Systems, Volume 89

Author(s): Jianhao Ding, Lansheng Han, Dan Li

Many issues in the cloud can be transformed into optimization problems, where data is of high dimension and randomness. Thus, stochastic optimizing is a key to Autonomous Cloud. And one of the most significant discussions in this field is how to adapt the learning rate and convergent path dynamically. This paper proposes a gradient-based algorithm called Adacom, that is based on an adaptive control system and momentum. Critically inheriting the previous studies, a reference model is introduced to generate the update. The method reduces noise and decides on paths with less oscillation, while maintaining the accumulated learning rate. Due to system design properties, the method requires fewer hyper-parameters for tuning. We state the prospect of Adacom as a general optimizer in Autonomous Cloud, and explore the potential of Adacom for pervasive computing by the assumption of transition data. Then we demonstrate the convergence of Adacom theoretically. The evaluations over the simulated transition data prove the feasibility and superiority of Adacom with other gradient-based methods.





资源原始URL http://rss.sciencedirect.com/action/redirectFile?&zone=main¤tActivity=feed&usageType=outward&url=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%3F_ob%3DGatewayURL%26_origin%3DIRSSSEARCH%26_method%3DcitationSearch%26_piikey%3DS0167739X17329989%26_version%3D1%26md5%3D5e281ee73efcede61902c1632759ce1f
资源来源机构: Elsevier
资源来源机构URL: http://rss.sciencedirect.com/getMessage?registrationId=JDGJJEGKQFGSKEGNLDHNJKHNJHIJLHKQSEIOJMJPSO
来源机构所属国家: 其他
来源机构性质:
您还没有登录。 请先登录再使用本系统。
您还没有登录。 请先登录再使用本系统。