Collective Neurodynamic Optimization Technology For Distributed Big Data Processing
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About The Author

Dr. Qingshan Liu is an assistant research professor in the Department of Computer Science, Computational Biomedicine Imaging & Modeling Center (CBIM), Rutgers, The State University of New Jersey since 2010. He received his PhD from the National Laboratory of Pattern Recognition, Chinese Academic of Science in 2003 and his MS from the Department of Auto Control in South-East University in 2000. Before he joined in Rutgers University, he worked as an associate professor at the National Laboratory of Pattern Recognition, Chinese Academic of Science, and he worked as an associate researcher at the Multimedia Laboratory in Chinese University of  Hong Kong during June, 2004 and April, 2005. He received the president scholarship of Chinese Academy of Sciences in 2003. His research interests are Image and Vision Analysis including Face Image Analysis, Graph & Hyper-graph based Image and Video understanding, Medical Image Analysis, Event-based Video Analysis, etc. He has published more than 80 papers in journals and conferences. He is an editorial board member of NeuroComputing and the Journal of Advance in Multimedia, and he is a guest editor of IEEE Transaction on Multimedia, Computer Vision & Image Understanding, and Pattern Recognition Letters. He is a senior member of the IEEE.

                       

Collective Neurodynamic Optimization Technology For Distributed Big Data Processing

With the development of artificial intelligence, especially in big data, machine learning and related areas, the size and complexity of modern datasets are increasing explosively. To solve these problems with a large-scale dataset, the distributed/decentralized computing frame has been proposed and well established. There are mainly two considerations for the distributed computing: The first one is that the data itself is stored distributedly due to the considering from the sense of data storing and security. In this case, the data must...

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