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香港图库香港资料库:Taming the Data Deluge

2012.09.24

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Speaker: essay writers online Qin Zhang

Time: 25 ?Sept, 2012 ? ?15:00

Venue: No.2 Meeting room, 102 Software Building, Zhangjiang Campus

Contact: 王晓阳 xywangCS@fudan.edu.cn

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Abstract:

There has been a spectacular increase in the amount of data being collected and processed in many modern applications, and traditional algorithms theory is ill-suited for handling such amount of data.

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In particular, traditional theory used simplistic machine models which are not suitable for modern computer architectures and applications, and the inadequacy of the simplistic machine models directly translates into deficiencies of software when processing massive data.

In this talk, I will try to address this issue by introducing several successful models for handling massive data. I will highlight the primary features they capture and the central issues we need to explore. I will then focus on one particular model - the distributed streaming model, provide an overview of the important and fundamental problems, and illustrate how to design and analyze efficient?algorithms in this model. All these works are strongly motivated by databases, data mining and network applications.

 

Bio:

Qin Zhang is currently a postdoctoral fellow in IBM Almaden Research?Center. He will join Indiana University Bloomington as an assistant?professor in 2013. He obtained his Ph.D. degree in Computer Science?and Engineering from Hong Kong University of Science and Technology in?2010, and his B.Sc. degree in Computer Science from Fudan University?in 2006. During 2010-2012 he was a postdoctoral fellow at Center for?Massive Data Algorithmics, Computer Science Department, Aarhus?University.

His current research interests include algorithms on big data; data?streams; algorithms on distributed data; data structures; external?memory algorithms; database algorithms; communication complexity.

 

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