从DNF压缩到正则性的向日葵定理
From DNF compression to sunflower theorems via regularity
摘要：
向日葵猜想是组合数学中最著名的公开问题之一。它在理论计算机科学中有几个应用，其中之一是DNF压缩，由于Gopalan，Meka和Reingold [计算复杂性2013]。在本文中，我们证明了DNF压缩的改进边界意味着向日葵猜想的改进边界，这是[计算复杂性2013]的相反方向。主要方法是基于集系统的正则性和向日葵猜想的结构与伪随机性方法。
英文摘要：
The sunflower conjecture is one of the most well-known open problems in combinatorics. It has several applications in theoretical computer science, one of which is DNF compression, due to Gopalan, Meka and Reingold [Computational Complexity 2013]. In this paper, we show that improved bounds for DNF compression imply improved bounds for the sunflower conjecture, which is the reverse direction of [Computational Complexity 2013]. The main approach is based on regularity of set systems and a structure-vs-pseudorandomness approach to the sunflower conjecture.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
