報(bào)告題目：Integer Least Squares Estimation: Theory and Algorithms
報(bào)告人：Dr. Jinming Wen (CNRS, Laboratoire LIP (U. Lyon, CNRS, ENSL,
INRIA, UCBL), France)
報(bào)告時(shí)間：2015年11月12日（周四）下午14:30-15:30
報(bào)告地點(diǎn)：X2511 (kaiyun開云官方網(wǎng)站學(xué)術(shù)報(bào)告廳
)
報(bào)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.
