Cognitive Computing Architectures for Machine (Deep) Learning at Scale

Proceedings

Mittal, Samir¹ 

关键词: machine learning;    cognitive computing;    distributed computing;    knowledge structures;    heterogeneous computing;   

DOI  :  10.3390/IS4SI-2017-04025

学科分类：社会科学、人文和艺术（综合）

来源: mdpi

【 摘 要 】

The paper reviews existing models for organizing information for machine learning systems in heterogeneous computing environments. In this context, we focus on structured knowledge representations as they have played a key role in enabling machine learning at scale. The paper highlights recent case studies where knowledge structures when combined with the knowledge of the distributed computation graph have accelerated machine-learning applications by 10 times or more. We extend these concepts to the design of Cognitive Distributed Learning Systems to resolve critical bottlenecks in real-time machine learning applications such as Predictive Analytics and Recommender Systems.

【 授权许可】

CC BY