{"id":3610,"date":"2015-10-24T07:29:48","date_gmt":"2015-10-24T07:29:48","guid":{"rendered":"http:\/\/smartdigitalcommunity.utm.my\/utmbigdata\/?p=3610"},"modified":"2016-06-15T17:29:23","modified_gmt":"2016-06-15T17:29:23","slug":"submission-deadline31-january-2016_call-for-papers-ijasca-special-issue-on-big-data-pattern-computing-and-analysis-of-machine-learning-algorithms","status":"publish","type":"post","link":"https:\/\/research.utm.my\/bdc\/2015\/10\/24\/submission-deadline31-january-2016_call-for-papers-ijasca-special-issue-on-big-data-pattern-computing-and-analysis-of-machine-learning-algorithms\/","title":{"rendered":"CALL FOR PAPERS_IJASCA:: EXTENDED SUBMISSION DEADLINE:-29 FEBRUARY 2016-“Special Issue on Big Data Pattern Computing and Analysis of Machine Learning Algorithms”"},"content":{"rendered":"

\"IJASCA_1feb2016\"<\/a><\/p>\n

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\nCALL FOR PAPERS<\/p>\n

International Journal of Advances in Soft Computing and its Application (IJASCA)<\/p>\n

Special Issue on<\/p>\n

Big Data Pattern Computing and Analysis of Machine Learning Algorithms\u00a0<\/strong><\/p>\n

http:\/\/www.home.ijasca.com\/special-issue\/<\/a><\/p>\n

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Machine learning (ML) algorithms are computationally expensive, especially on the typical central processing unit (CPU) environment. The growing births of new intelligent system architectures are often due to the multi strategy learning and adaptation of advanced soft computing techniques in various fields such as pattern recognition, and data mining, particularly to address the issues of Big Data.\u00a0 Big data computing needs advanced technologies or methods to solve the issues of computational time to extract valuable information, in a realistic and practical time frame, without compromising the models quality.\u00a0 Therefore, high performance hardware with the potential to yield remarkable performance gains, as compared to the CPU, is plausible to accomplish faster solutions to address Big Data.<\/p>\n

This special issue aims to bring together research work in the area of Big Data Computing for machine learning algorithms in solving complex problems of N-dimensional.<\/p>\n

Topics:<\/strong><\/p>\n

The paper may focus on high performance computing for machine learning algorithms and theory in big data problems. The scopes of the topics include but are not limited to:<\/p>\n

SCOPE 1: Machine Learning Algorithms for Big Data<\/p>\n