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学术报告:Big Data Challenges, Techniques,and Applications and How Deep Learning Can be Used


发布日期:2016-04-27 浏览数:

报告人:C. L. Philip CHEN 陳俊龍教授,澳门大学科技学院院长,澳门大学讲座教授,IEEE Fellow, AAAS Fellow, CAA Fellow, HKIE Fellow, IASCYS Academician, IEEE Transactions on Systems, Man and Cybernetics: Systems的Editor-in-Chief(主编),IEEE Systems, Man, and Cybernetics Society (系统、人机及智能自动学会)2012-2014年President(理事长)。

地点:学术交流中心(前湖大厦)二层多功能厅

时间:2015年5月6日上午8:30

报告简介:It is already true that Big Data has drawn huge attention from researchers in information sciences, policy and decision makers in governments and enterprises. A large number of fields and sectors, ranging from economic and business activities to public administration, from national security to scientific researches in many areas, involve with Big Data problems. This talk is aimed to demonstrate a close-up view about Big Data, including Big Data applications, Big Data opportunities and challenges, as well as the state-of-the-art techniques and technologies that we currently adopt to deal with the Big Data problems. The second part is to discuss the deep learning role in Big Data. In recent years, deep learning caves out a research wave in machine learning. With outstanding performance, more and more applications of deep learning in pattern recognition, image recognition, speech recognition, and video processing have been developed. Restricted Boltzmann machine (RBM) plays an important role in current deep learning techniques, as most of existing deep networks are based on or related to it. This talk will also discuss how the big data relates with the deep learning.
信息工程学院
2016年4月27日
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