Web2 mei 2024 · Concentration inequality 刻画了一组随机变量的和（或者样本平均数）与其期望值的偏离程度，在算法收敛性分析过程中是非常有用的一类不等式。 这次主要总结一下最近一段时间遇到的集中不等式，不仅是不等式形式，也有不等式之间的相互关系的归纳总 … WebWe prove a Chernoff-type bound for sums of matrix-valued random variables sampled via a regular (aperiodic and irreducible) finite Markov chain. Specially, consider a random …
Scalar and Matrix Chernoff Bounds from ℓ_∞-Independence
Webindependent random variables around their mean. We will start with the inequalities of Markov, Cherno and Hoe ding and end with the logarithmic Sobolev inequalities of Ledoux. We will also discuss other inequalities that apply to Gaussian processes. The focus will be on inequalities that play a role in applications to signal WebMatrix-valued Probabilistic Inequalities Low rank matrix-valued chernoff bound Approximate Matrix Multiplication via row sampling and random projections Applications: … jenny yun lightly row
Inégalité de Chernoff — Wikipédia
Web15 sep. 2008 · A matrix variance inequality. Journal of Statistical Planning and Inference 130, 351–358] obtained an inequality for the covariance matrix of k functions. However, … Webthe last decade, with the advent of matrix concentration inequalities, research has advanced to the point where we can conquer many (formerly) challenging problems with … Web$\begingroup$ You are right, that one doesn't require positive matrices. I was making the $4 \times 4$ matrix in order to consider the other inequalities on that page. It is also possible to put the real and imaginary parts on the diagonal of a $2 \times 2$ matrix, but again it doesn't seem to improve the bound. $\endgroup$ – jenny yoo maternity bridesmaid dresses