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Related papers: On problems equivalent to (min,+)-convolution

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In this work we consider the problem of computing the $(\min, +)$-convolution of two sequences $a$ and $b$ of lengths $n$ and $m$, respectively, where $n \geq m$. We assume that $a$ is arbitrary, but $b_i = f(i)$, where $f(x) \colon [0,m)…

Computational Complexity · Computer Science 2022-09-29 D. V. Gribanov , I. A. Shumilov , D. S. Malyshev

The \Problem{knapsack} problem is a fundamental problem in combinatorial optimization. It has been studied extensively from theoretical as well as practical perspectives as it is one of the most well-known NP-hard problems. The goal is to…

Computer Science and Game Theory · Computer Science 2018-12-03 MohammadHossein Bateni , MohammadTaghi Hajiaghayi , Saeed Seddighin , Cliff Stein

In the Knapsack problem, one is given the task of packing a knapsack of a given size with items in order to gain a packing with a high profit value. An important connection to the $(\max,+)$-convolution problem has been established, where…

Data Structures and Algorithms · Computer Science 2025-08-12 Kilian Grage , Klaus Jansen , Björn Schumacher

Given a sequence of n numbers, the Maximum Consecutive Subsums Problem (MCSP) asks for the maximum consecutive sum of lengths l for each l = 1,...,n. No algorithm is known for this problem which is significantly better than the naive…

Data Structures and Algorithms · Computer Science 2015-09-21 Wilfredo Bardales Roncalla , Eduardo Laber , Ferdinando Cicalese

Exponential-time approximation has recently gained attention as a practical way to deal with the bitter NP-hardness of well-known optimization problems. We study for the first time the $(1 + \varepsilon)$-approximate min-sum subset…

Data Structures and Algorithms · Computer Science 2024-08-12 Mihail Stoian

Approximating Subset Sum is a classic and fundamental problem in computer science and mathematical optimization. The state-of-the-art approximation scheme for Subset Sum computes a $(1-\varepsilon)$-approximation in time…

Data Structures and Algorithms · Computer Science 2020-10-28 Karl Bringmann , Vasileios Nakos

Theoretical studies on evolutionary algorithms have developed vigorously in recent years. Many such algorithms have theoretical guarantees in both running time and approximation ratio. Some approximation mechanism seems to be inherently…

Neural and Evolutionary Computing · Computer Science 2022-10-04 Yaoyao Zhang , Chaojie Zhu , Shaojie Tang , Ringli Ran , Ding-Zhu Du , Zhao Zhang

We prove 3SUM-hardness (no strongly subquadratic-time algorithm, assuming the 3SUM conjecture) of several problems related to finding Abelian square and additive square factors in a string. In particular, we conclude conditional optimality…

Data Structures and Algorithms · Computer Science 2021-07-21 Jakub Radoszewski , Wojciech Rytter , Juliusz Straszyński , Tomasz Waleń , Wiktor Zuba

In the classical Subset Sum problem we are given a set $X$ and a target $t$, and the task is to decide whether there exists a subset of $X$ which sums to $t$. A recent line of research has resulted in $\tilde{O}(t)$-time algorithms, which…

Data Structures and Algorithms · Computer Science 2023-04-25 Karl Bringmann , Vasileios Nakos

Knapsack and Partition are two important additive problems whose fine-grained complexities in the $(1-\varepsilon)$-approximation setting are not yet settled. In this work, we make progress on both problems by giving improved algorithms. -…

Data Structures and Algorithms · Computer Science 2023-01-24 Mingyang Deng , Ce Jin , Xiao Mao

The field of fine-grained complexity aims at proving conditional lower bounds on the time complexity of computational problems. One of the most popular assumptions, Strong Exponential Time Hypothesis (SETH), implies that SAT cannot be…

Computational Complexity · Computer Science 2023-07-24 Tatiana Belova , Alexander S. Kulikov , Ivan Mihajlin , Olga Ratseeva , Grigory Reznikov , Denil Sharipov

In this paper, we introduce a general framework for fine-grained reductions of approximate counting problems to their decision versions. (Thus we use an oracle that decides whether any witness exists to multiplicatively approximate the…

Data Structures and Algorithms · Computer Science 2020-11-25 Holger Dell , John Lapinskas

Consider positive integral solutions $x \in \mathbb{Z}^{n+1}$ to the equation $a_0 x_0 + \ldots + a_n x_n = t$. In the so called unbounded subset sum problem, the objective is to decide whether such a solution exists, whereas in the…

Data Structures and Algorithms · Computer Science 2021-08-13 Kim-Manuel Klein

We develop approximation algorithms for set-selection problems with deterministic constraints, but random objective values, i.e., stochastic probing problems. When the goal is to maximize the objective, approximation algorithms for probing…

Data Structures and Algorithms · Computer Science 2021-11-04 Weina Wang , Anupam Gupta , Jalani Williams

Given an $n*n$ sparse symmetric matrix with $m$ nonzero entries, performing Gaussian elimination may turn some zeroes into nonzero values. To maintain the matrix sparse, we would like to minimize the number $k$ of these changes, hence…

Computational Complexity · Computer Science 2016-06-28 Yixin Cao , R. B. Sandeep

The 3SUM problem is one of the cornerstones of fine-grained complexity. Its study has led to countless lower bounds, but as has been sporadically observed before -- and as we will demonstrate again -- insights on 3SUM can also lead to…

Data Structures and Algorithms · Computer Science 2024-10-29 Nick Fischer , Ce Jin , Yinzhan Xu

Evolutionary algorithms are well suited for solving the knapsack problem. Some empirical studies claim that evolutionary algorithms can produce good solutions to the 0-1 knapsack problem. Nonetheless, few rigorous investigations address the…

Neural and Evolutionary Computing · Computer Science 2014-10-07 Jun He , Boris Mitavskiy , Yuren Zhou

The $3$SUM hypothesis, the APSP hypothesis and SETH are the three main hypotheses in fine-grained complexity. So far, within the area, the first two hypotheses have mainly been about integer inputs in the Word RAM model of computation. The…

Computational Complexity · Computer Science 2022-04-15 Timothy M. Chan , Virginia Vassilevska Williams , Yinzhan Xu

We present a pseudopolynomial-time algorithm for the Knapsack problem that has running time $\widetilde{O}(n + t\sqrt{p_{\max}})$, where $n$ is the number of items, $t$ is the knapsack capacity, and $p_{\max}$ is the maximum item profit.…

Data Structures and Algorithms · Computer Science 2024-07-02 Karl Bringmann , Anita Dürr , Adam Polak

We introduce several generalizations of classical computer science problems obtained by replacing simpler objective functions with general submodular functions. The new problems include submodular load balancing, which generalizes load…

Data Structures and Algorithms · Computer Science 2010-06-02 Zoya Svitkina , Lisa Fleischer
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