Faster Convolutions: Yates and Strassen Revisited

TL;DR

This paper introduces a new multilinear algebra perspective on product-domain convolutions, leading to improved algorithms with sub-quadratic time complexity, and discusses implications of Strassen's conjecture for future algorithmic efficiency.

Contribution

It provides a novel multilinear algebra framework for analyzing product-domain convolutions and derives improved algorithms based on matrix multiplication theory.

Findings

Achieves $O(|D|^{1.582})$ time complexity for convolutions.

Reinterprets existing algorithms through multilinear algebra.

Connects convolution complexity to Strassen's asymptotic rank conjecture.

Abstract

Given two vectors $u,v \in \mathbb{Q}^D$ over a finite domain $D$ and a function $f : D\times D\to D$, the convolution problem asks to compute the vector $w \in \mathbb{Q}^D$ whose entries are defined by $w(d) = \sum_{\substack{x,y \in D \\ f(x,y)=d}} u(x)v(y).$ In parameterized and exponential-time algorithms, convolutions on product domains are particularly prominent: Here, a finite domain $B$ and a function $h : B \times B \to B$ are fixed, and convolution is done over the product domain $D = B^k$, using the function $h^k :D \times D\to D$ that applies $h$ coordinate-wise to its input tuples. We present a new perspective on product-domain convolutions through multilinear algebra. This viewpoint streamlines the presentation and analysis of existing algorithms, such as those by van Rooij et al. (ESA 2009). Moreover, using established results from the theory of fast matrix multiplication, we derive improved $O^\ast(|B|^{2\omega/3 \cdot k}) = O(|D|^{1.582})$ time algorithms, improving upon previous upper bounds by Esmer et al. (Algorithmica 86(1), 2024) of the form $c^k |B|^{2k}$ for $c < 1$. Using the setup described in this note, Strassen's asymptotic rank conjecture from algebraic complexity theory would imply quasi-linear $|D|^{1+o(1)}$ time algorithms. This conjecture has recently gained attention in the algorithms community. (Bj\"orklund-Kaski and Pratt, STOC 2024, Bj\"orklund et al., SODA 2025) Our paper is intended as a self-contained exposition for an algorithms audience, and it includes all essential mathematical prerequisites with explicit coordinate-based notation. In particular, we assume no knowledge in abstract algebra.