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                                                     Seminar

             Department of Systems Engineering and Engineering Management
                                  The Chinese University of Hong Kong

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Title

:

Some results on binary and nonconvex quadratic programming

　

　

　

Speaker

:

Prof. Jiming Peng

　

　

Industrial and enterprise system engineering,

　

　

University of Illinois at Urbana-Champaign.

　

　

　

Date

:

June 26th, 2009 (Friday)

　

　

　

Time

:

4:30 p.m. - 5:30 p.m.

　

　

　

Venue

:

Room 513

　

　

William M.W. Mong Engineering Building

　

　

(Engineering Building Complex Phase 2)

　

　

CUHK

　

　

　

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Abstract:
　

Binary and nonconvex quadratic programming is one of the most popular optimization models that has been intensively studied and widely applied in a broad range of disciplines. Nevertheless, there still exist many challenging issues in the study of binary and nonconvex quadratic programming problems. In this talk, we report some recent results on a few special classes of binary and nonconvex QPs including the quadratic assignment problem, the densest k-subgraph problem and the standard QP over simplex. In particular, we focus on how to use the structure in the input data to derive simple and strong relaxations for QAPs, use ggeometric embedding to transfer the densest k-subgraph problem into a specific clustering problem and then design effective approximation algorithms for the clustering problem. If time allows, we shall also discuss the existence of sparse solutions to nonconvex QPs over simplex.


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Biography:
　

Jiming Peng received his PhD degree in information and system in Delft University of Technology, the Netherlands, 2001. Then, he worked in the department of computing and software engineering in McMaster University from 2001-2006. He moved to the department of industrial and enterprise system engineering of University of Illinois at Urbana-Champaign in 2006. His research interest covers several areas in the field of mathematical programming such as numercial methods for complementarity and variational inequalities, interior-point methods for linear conic optimization, approximation algorithms for discrete optimization and optimization modeling and resolution in data mining and machine learning. He has published over 30 scientific paper in peer reviewed journals and a research monography by Princeton University Press. He has been serving as an associate editor for the Springer journal ``Optimization Letters\'\' since 2006. He is also a co-editor for the special issue (Optimization Methods and Software) on Mathematical Prgramming in Data Mining and Machine Learning.

He is a recipient of the Stieljes Prize for the best thesis in the Netherlands, 2001, a finalist of the K. Tucker prize awarded by the mathematical programming society in 2003, and a recipient of the Premier Research Excellence award from Ontario, Canada in 2003.


************************* ALL ARE WELCOME ************************

　

　

　

Host

:

Prof. Shuzhong Zhang

Tel

:

(852) 2609-8240

Email

:

zhang@se.cuhk.edu.hk

　

　

　

Enquiries

:

Prof. Nan Chen or Prof. Sean X. Zhou

　

:

Department of Systems Engineering and Engineering Management

　

　

CUHK

Website

:

http://www.se.cuhk.edu.hk/~seg5810

Email

:

seg5810@se.cuhk.edu.hk

　

　

　

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