Fourier meets M\"{o}bius: fast subset convolution
Andreas Bj\"orklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto

TL;DR
This paper introduces a significantly faster algorithm for subset convolution using Möbius transform, enabling efficient computations over various semirings and improving solutions for problems like the minimum Steiner tree.
Contribution
The authors develop an O^*(2^n log M) time algorithm for subset convolution over sum-product rings and extend it to max-sum and min-sum semirings, with applications to graph problems.
Findings
Achieved O(n^2 2^n) complexity for subset convolution.
Improved minimum Steiner tree algorithm to O^*(2^k n^2 + n m).
Extended techniques to cover partitioning problems.
Abstract
We present a fast algorithm for the subset convolution problem: given functions f and g defined on the lattice of subsets of an n-element set N, compute their subset convolution f*g, defined for all S\subseteq N by (f * g)(S) = \sum_{T \subseteq S}f(T) g(S\setminus T), where addition and multiplication is carried out in an arbitrary ring. Via M\"{o}bius transform and inversion, our algorithm evaluates the subset convolution in O(n^2 2^n) additions and multiplications, substantially improving upon the straightforward O(3^n) algorithm. Specifically, if the input functions have an integer range {-M,-M+1,...,M}, their subset convolution over the ordinary sum-product ring can be computed in O^*(2^n log M) time; the notation O^* suppresses polylogarithmic factors. Furthermore, using a standard embedding technique we can compute the subset convolution over the max-sum or min-sum semiring in…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Algorithms and Data Compression · Computational Geometry and Mesh Generation
