Title: Statistical Dependency and Fast Computing
地點(diǎn)：良鄉(xiāng)1-108室
時(shí)間：6月24日上午9點(diǎn)50分-10點(diǎn)50分
報(bào)告人：Xiaoming Huo, 霍曉明   Georgia Institute of Technology and National Science Foundation

      We consider computation of statistical dependence measures that are based on pairwise distances. Distance correlation had been introduced as a better alternative to the celebrated Pearson’s correlation. The existing algorithm for the distance correlation seemingly requires an O(n^2) algorithm, and I will show how it can be done in O(n log n). Moreover, many other statistical dependency related quantities can be computed efficiently. I will give some other examples. This talk is based on a joint work with Dr. Gabor Szekely.