Improved Space-Time Tradeoffs for kSUM
Isaac Goldstein, Moshe Lewenstein, Ely Porat

TL;DR
This paper advances the understanding of time-space tradeoffs for the kSUM problem by introducing new algorithms with improved bounds, including specialized solutions for 3SUM and 6SUM, using self-reduction techniques.
Contribution
It presents improved algorithms for kSUM with better time-space tradeoffs, utilizing a novel self-reduction from kSUM to mSUM, and offers specialized solutions for 3SUM and 6SUM.
Findings
Las Vegas solution with $O(n^{k- ext{delta}\sqrt{2k}})$ time and $O(n^{ ext{delta}})$ space.
Deterministic solution with $O(n^{k- ext{delta}\sqrt{k}})$ time and $O(n^{ ext{delta}})$ space.
Efficient 6SUM algorithm with $O(n^4)$ time and $O(n^{2/3})$ space.
Abstract
In the kSUM problem we are given an array of numbers and we are required to determine if there are different elements in this array such that their sum is 0. This problem is a parameterized version of the well-studied SUBSET-SUM problem, and a special case is the 3SUM problem that is extensively used for proving conditional hardness. Several works investigated the interplay between time and space in the context of SUBSET-SUM. Recently, improved time-space tradeoffs were proven for kSUM using both randomized and deterministic algorithms. In this paper we obtain an improvement over the best known results for the time-space tradeoff for kSUM. A major ingredient in achieving these results is a general self-reduction from kSUM to mSUM where , and several useful observations that enable this reduction and its implications. The main results we prove in this paper…
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