Quickly Finding Orthogonal Vectors and Hamming Nearest Neighbors
Speaker: JoshTitle: Quickly Finding Orthogonal Vectors and Hamming Nearest Neighbors
Date: 20 Apr 2020 12:00pm-1:00pm
Location: Zoom
Food: Self-prepared
Zoom link: https://harvard.zoom.us/j/978937656
Abstract: In the Orthogonal Vectors problem, we are given as input n vectors from {0,1}^d for d = O(log n), and we want to determine whether any pair of them are orthogonal (over Z). In the Hamming Nearest Neighbors problem, we instead want to find the pair of vectors which is closest in Hamming distance. Both of these problems have simple algorithms that run in about quadratic time in n, and a popular conjecture from fine-grained complexity (the Strong Exponential Time Hypothesis (SETH)) implies that one cannot improve this by too much. In this talk, I’ll present faster algorithms which solve these problems about as quickly as possible without refuting SETH: we’ll see that for every c>0, there is an eps>0 such that both problems in dimension d = c*log n can be solved in time O(n^{2-eps}). The algorithms will combine fast rectangular matrix multiplication with techniques from “the polynomial method”. The algorithms I’ll present are from [Abboud, Williams, Yu ‘15], [Alman, Williams ‘15], and [Alman, Chan, Williams ‘16] .