University of California, Riverside

Department of Electrical and Computer Engineering



Sampling and Modeling of Large-scale Networked Data


Sampling and Modeling of Large-scale Networked Data
 
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Sampling and Modeling of Large-scale Networked Data

March 17, 2014 - 11:00 am
Winston Chung Hall, 205/206

Abstract

Overthe past decade, the astonishing evolution of devices and materials has altered the landscape of sensing technologies -- both in a physical sense (e.g., bio-inspired mini-robots) and in a virtual sense (e.g., online social networks). The relentless scaling of these sensing agents provides us unprecedented amounts of networked data which are high-dimensional, heterogeneous, complex, and uncertain. Standing at the beginning of a data-concentric era, we seek to harness these data and build intelligent systems to improve decision makings.

In this talk, I will focus on two fundamental signal processing problems arising from analyzing large-scale networked data. First, I will present a sampling framework that can effectively estimate signals from a small subset of samples. The new framework is warranted with statistical guarantee, and is accompanied with optimal sampling schemes. I will use image denoising as an example application. Second, I will present a modeling framework for a class of information networks. The new model, termed a graphon, subsumes a number of popular parametric network models and offers greater modeling flexibility. I will present two statistically consistent graphon estimation methods, and demonstrate their applications in network comparisons. 

Biography

Ho (Stanley) Chan is a post-doctoral research fellow in the School of Engineering and Applied Science and the Department of Statistics of Harvard University. He received the B.Eng. degree in Electrical Engineering (with first class honor) from the University of Hong Kong in 2007, the M.A. degree in Mathematics from University of California, San Diego in 2009, and the Ph.D. degree in Electrical Engineering from University of California, San Diego in 2011. His current research interests are statistical signal processing and graph theory, with applications in imaging and network analysis. Dr. Chan is a recipient of the Croucher Foundation Fellowship for Post-doctoral Research 2012-2013 and the Croucher Foundation Scholarship for Full-time Overseas PhD Studies 2008-2010, one of the most prestigious scholarships for outstanding Hong Kong students studying overseas.

 

 

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University of California, Riverside
900 University Ave.
Riverside, CA 92521
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Electrical and Computer Engineering
Suite 343 Winston Chung Hall
University of California, Riverside
Riverside, CA 92521-0429

Tel: (951) 827-2484
Fax: (951) 827-2425
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