A short tutorial on negative dependence, with applications to multiple testing
Speaker: Aaditya Ramdas
Abstract: What does it mean for a vector of random variables to be "negatively dependent"? We'll look at various definitions from the literature, and examples of when they arise (multinomials, permutations, sampling without replacement, tournaments). This will be based on some recent work with Ziyu Chi and Ruodu Wang https://arxiv.org/pdf/2212.09706.pdf, which proves the first known (and possibly surprising) results for multiple testing under negative dependence. We'll end with a few ripe open problems.