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    温金明博士学术报告

    2015-11-11 郝虹 点击:[]

    报告题目:Integer Least Squares Estimation: Theory and Algorithms

    报告人:Dr. Jinming Wen  (CNRS, Laboratoire LIP (U. Lyon, CNRS, ENSL,
                      INRIA, UCBL), France)

    报告时间:20151112日(周四)下午14:30-15:30

    报告地点:X2511 (新葡萄8883官网AMG学术报告厅)

    报告摘要:

    Integer leastsquares (ILS) problems, also referred to as closest vector problems, havearisen from many applications such as GPS, wireless communications,cryptanalysis, bioinformatics etc. A general ILS problem is NP-hard. In this talk, we review some theory and algorithms for ILS. We first introduce two theoretical results we recently obtained, which rigorously justify the use of the well-known Lenstra, Lenstra and Lovasz (LLL) reduction as preprocessing for solving ordinary ILS problem. We then introduce some lower bound techniques to reduce the cost of solving the ILS. Finally, we introduce some other types of ILS and some future research problems.


     

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