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 MA Shilong,WUNIRI Qiqige,LI Xiaoping.Deep learning with big data: state of the art and development[J].CAAI Transactions on Intelligent Systems,2016,11(6):728-742.[doi:10.11992/tis.201611021]





Deep learning with big data: state of the art and development
马世龙 乌尼日其其格 李小平
北京航空航天大学 软件开发环境国家重点实验室, 北京 100191
MA Shilong WUNIRI Qiqige LI Xiaoping
State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China
big datamachine learningdeep networkdeep learningneural networkartificial intelligencelearning algorithmderivation tree
As the era of the big data arrives, it is accompanied by profound changes to traditional data science based on statistics. Big data also pushes innovations in the methods of data analysis. Deep learning that evolves from machine learning and multilayer neural networks are currently extremely active research areas. From the symbolic machine learning and statistical machine learning to the artificial neural network, followed by data mining in the 90s, this has built a solid foundation for deep learning (DL) that makes it a notable tool for discovering the potential value behind big data. This survey compactly summarized big data and DL, proposed a generative relationship tree of the major deep networks and the algorithms, illustrated a broad area of applications based on DL, and highlighted the challenges to DL with big data, as well as identified future trends.


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