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隐团和隐子阵问题的改进平方和下界

Improved Sum-of-Squares Lower Bounds for Hidden Clique and Hidden Submatrix Problems
课程网址: https://videolectures.net/videos/colt2015_deshpande_submatrix_pro...  
主讲教师: Yash Deshpande
开课单位: 信息不详。欢迎您在右侧留言补充。
开课时间: 2025-02-04
课程语种: 英语
中文简介:
给定一个大数据矩阵$ a \in\实数^{n\乘以n}$,我们考虑确定其元素是否为已知边际分布$ a的i.i.d的问题_{ij} \ sim P_0$,或者代替$A$包含主子矩阵$A_{\sC,\sC}$,其项具有边际分布$A_{ij} \ sim P_1 \ neq P_0美元。作为一种特殊情况,隐藏(或种植)团问题是在均匀随机图中找到一个种植的团。假设计算资源无界,只要$|\sC|\ge C \log n$为合适的常数$C$,这个假设检验问题在统计上是可解的。然而,尽管付出了巨大的努力,当$|\sC| = 0 (\sqrt{n})$时,没有已知的多项式时间算法高概率成功。最近,\cite{meka2013association}提出了一种在平方和(SOS)半确定层次结构中建立隐团问题下界的方法。这里我们考虑度-$4$ SOS松弛,并研究构造\cite{meka2013} association来证明除非$k\ge C\, n^{1/3}/\log n$,否则SOS失效。\cite{BarakLectureNotes}提出的一个论点表明,除非在证明中改变证人构造,否则这个下界不能得到实质性的改进。我们的证明使用矩量法来约束一个随机关联方案的谱,即一个对称随机矩阵,其行和列由Erd\ os-Renyi随机图的边索引。
课程简介: Given a large data matrix $A\in\reals^{n\times n}$, we consider the problem of determining whether its entries are i.i.d. with some known marginal distribution $A_{ij}\sim P_0$, or instead $A$ contains a principal submatrix $A_{\sC,\sC}$ whose entries have marginal distribution $A_{ij}\sim P_1\neq P_0$. As a special case, the hidden (or planted) clique problem is finding a planted clique in an otherwise uniformly random graph. Assuming unbounded computational resources, this hypothesis testing problem is statistically solvable provided $|\sC|\ge C \log n$ for a suitable constant $C$. However, despite substantial effort, no polynomial time algorithm is known that succeeds with high probability when $|\sC| = o(\sqrt{n})$. Recently, \cite{meka2013association} proposed a method to establish lower bounds for the hidden clique problem within the Sum of Squares (SOS) semidefinite hierarchy. Here we consider the degree-$4$ SOS relaxation, and study the construction of \cite{meka2013association} to prove that SOS fails unless $k\ge C\, n^{1/3}/\log n$. An argument presented by \cite{BarakLectureNotes} implies that this lower bound cannot be substantially improved unless the witness construction is changed in the proof. Our proof uses the moment method to bound the spectrum of a certain random association scheme, i.e. a symmetric random matrix whose rows and columns are indexed by the edges of an Erd\"os-Renyi random graph.
关 键 词: 大数据矩阵; 主子矩阵; 隐团问题
课程来源: 视频讲座网
数据采集: 2025-03-30:zsp
最后编审: 2025-03-30:zsp
阅读次数: 1