发表机构
Duke University; Harvard T.H. Chan School of Public Health(杜克大学; 哈佛陈曾熙公共卫生学院)
机构由 AI 辅助整理,请以论文原文为准。AI 中文总结
本文提出一种谱符号算法,在多项式时间内以常数差异解决Komlós问题,通过最小化三次谱势实现,时间复杂度为$O((mn^9+n^{10})\log(2+m+n))$。
AI 中文摘要
我们提出一种谱符号算法,在多项式时间内以常数差异解决Komlós问题。给定矩阵$A\in\mathbb{R}^{m\times n}$,其列向量的欧几里得范数至多为1,该算法找到一个向量$\varepsilon\in\{-1,1\}^n$,满足$\\|A\varepsilon\\|_\infty\le C$,其中$C$为绝对常数。通过最小化三次谱势,我们的谱符号算法将分数着色更新为布尔符号,时间复杂度为$O((mn^9+n^{10})\log(2+m+n))$。
英文摘要
We present a spectral signing algorithm solving the Komlós problem with a constant discrepancy in polynomial time. Given a matrix $A\in\mathbb{R}^{m\times n}$ whose columns have Euclidean norm at most $1$, the algorithm finds a vector $\varepsilon\in\{-1,1\}^n$ satisfying $\|A\varepsilon\|_\infty\le C$, where $C$ is an absolute constant. By minimizing a cubic spectral potential, our spectral signing algorithm updates the fractional coloring toward Boolean signs with time complexity $O((mn^9+n^{10})\log(2+m+n))$.
Comments20 pages, no figures