Parallel learning: a perspective and a framework
Li li; Yilun Lin; Nanning Zheng; Fei-Yue Wang
Source PublicationIEEE/CAA Journal of Automatica Sinica
2017
Volume4Issue:3Pages:389-395
Abstract
; The development of machine learning in complex system is hindered by two problems nowadays.The first problem is the inefficiency of exploration in state and action space, which leads to the data-hungry of some state-of-art data-driven algorithm.The second problem is the lack of a general theory which can be used to analyze and implement a complex learning system.In this paper,we proposed a general methods that can address both two issues.We combine the concepts of descriptive learning,predictive learning,and prescriptive learning into a uniform framework,so as to build a parallel system allowing learning system improved by self-boosting.Formulating a new perspective of data,knowledge and action,we provide a new methodology called parallel learning to design machine learning system for real-world problems.
KeywordDescriptive Learning Machine Learning Parallel Learning Parallel Systems Perspective Learning Perspective-learning
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/20162
Collection复杂系统管理与控制国家重点实验室_先进控制与自动化
Recommended Citation
GB/T 7714
Li li,Yilun Lin,Nanning Zheng,et al. Parallel learning: a perspective and a framework[J]. IEEE/CAA Journal of Automatica Sinica,2017,4(3):389-395.
APA Li li,Yilun Lin,Nanning Zheng,&Fei-Yue Wang.(2017).Parallel learning: a perspective and a framework.IEEE/CAA Journal of Automatica Sinica,4(3),389-395.
MLA Li li,et al."Parallel learning: a perspective and a framework".IEEE/CAA Journal of Automatica Sinica 4.3(2017):389-395.
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