from    
to    
search  

 


地球系统数值模拟教育部重点实验室2023年学术年会暨学术委员会会议
物理系colloquium: 双层扭转光晶格中的原子玻色爱因斯坦凝聚
学堂班系列讲座:“化学和计算驱动的功能蛋白质组学”
用于辐射检测的卤化铅钙钛矿纳米晶和纳米复合材料的最新进展
报告题目:
Quadratic Lower Bounds on Matrix Rigidity
 报告人:
Prof Satya Lokam
Microsoft Research
报告时间:
2005-11-16 10:30
报告地点:
FIT楼1-222
主办单位:
姚期智教授组
  简介:

Title: Quadratic Lower Bounds on Matrix Rigidity

 

Speaker: Prof Satya Lokam  (Microsoft Research)

 

Place: Room 1-222, FIT Building         

Time: 10:30am, Nov 16

 

Abstract: The rigidity of a matrix $A$ with respect to the rank bound $r$ is the minimum number of entries of $A$ that must be changed to reduce the rank of $A$ to or below $r$. It is a major unsolved problem (Valiant, 1977) to construct ``explicit" families of $n \times n$ matrices of rigidity $n^{1+\delta}$ for $r=\epsilon n$ where $\epsilon$ and $\delta$ are positive constants. In fact, no superlinear lower bounds are known for explicit families of matrices for rank bound $r=\Omega(n)$.

 

We will present the first optimal, $\Omega(n^2)$, lower bound on the rigidity of two ``somewhat explicit" families of matrices with respect to the rank bound $r= cn$, where $c$ is an absolute positive constant. The entries of these matrix families are (i) square roots of the first $n^2$ primes and (ii) primitive roots of unity of prime orders for the first $n^2$ primes. Our proofs use an algebraic dimension concept introduced by Shoup and Smolensky (1997) and a generalization of that concept.

 

今日相关信息
超越材料性能的自然极限
 
同类别相关信息
Web of Science 引文数据库的检索与利用
中文电子期刊数据库检索与利用
『清华信息大讲堂』第 40 讲:Network ...
清华大学学术信息资源门户使用
馆藏书刊检索与获取
学术活动