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We consider the approximate pattern matching problem under the edit distance. Given a text $T$ of length $n$, a pattern $P$ of length $m$, and a threshold $k$, the task is to find the starting positions of all substrings of $T$ that can be…

Data Structures and Algorithms · Computer Science 2022-04-08 Panagiotis Charalampopoulos , Tomasz Kociumaka , Philip Wellnitz

We show a close connection between structural hardness for $k$-partite graphs and tight inapproximability results for scheduling problems with precedence constraints. Assuming a natural but nontrivial generalisation of the bipartite…

Computational Complexity · Computer Science 2015-07-08 Abbas Bazzi , Ashkan Norouzi-Fard

This paper develops a data-driven, constraint-based optimization framework for a complex industrial job shop scheduling problem variant in pharmaceutical manufacturing. The formulation captures fixed routings and designated machines,…

We present a novel parallelisation scheme that simplifies the adaptation of learning algorithms to growing amounts of data as well as growing needs for accurate and confident predictions in critical applications. In contrast to other…

Machine Learning · Computer Science 2018-10-09 Michael Kamp , Mario Boley , Olana Missura , Thomas Gärtner

Coflow is a network abstraction used to represent communication patterns in data centers. The coflow scheduling problem encountered in large data centers is a challenging $\mathcal{NP}$-hard problem. This paper tackles the scheduling…

Data Structures and Algorithms · Computer Science 2023-12-29 Chi-Yeh Chen

Packing and covering linear programs (PC-LPs) form an important class of linear programs (LPs) across computer science, operations research, and optimization. In 1993, Luby and Nisan constructed an iterative algorithm for approximately…

Data Structures and Algorithms · Computer Science 2018-02-28 Zeyuan Allen-Zhu , Lorenzo Orecchia

Optimal transportation, or computing the Wasserstein or ``earth mover's'' distance between two distributions, is a fundamental primitive which arises in many learning and statistical settings. We give an algorithm which solves this problem…

Data Structures and Algorithms · Computer Science 2019-06-04 Arun Jambulapati , Aaron Sidford , Kevin Tian

We give the first input-sparsity time algorithms for the rank-$k$ low rank approximation problem in every Schatten norm. Specifically, for a given $n\times n$ matrix $A$, our algorithm computes $Y,Z\in \mathbb{R}^{n\times k}$, which, with…

Data Structures and Algorithms · Computer Science 2020-07-01 Yi Li , David Woodruff

We revisit the complexity of the classical Interval Scheduling in the dynamic setting. In this problem, the goal is to maintain a set of intervals under insertions and deletions and report the size of the maximum size subset of pairwise…

Data Structures and Algorithms · Computer Science 2022-10-04 Paweł Gawrychowski , Karol Pokorski

In algorithmic graph theory, a classic open question is to determine the complexity of the Maximum Independent Set problem on $P_t$-free graphs, that is, on graphs not containing any induced path on $t$ vertices. So far, polynomial-time…

Data Structures and Algorithms · Computer Science 2018-04-12 Gábor Bacsó , Daniel Lokshtanov , Dániel Marx , Marcin Pilipczuk , Zsolt Tuza , Erik Jan van Leeuwen

We consider a 1-machine scheduling problem where the temperature of a job rises during processing, and cools down when not being processed according to given linear heating and cooling rates. No job's temperature is allowed to rise above a…

Optimization and Control · Mathematics 2023-12-18 Roel Lambers , Rudi Pendavingh , Frits Spieksma , Céline M. F. Swennenhuis

Consider the classical Min-Sum Set Cover problem: We are given a universe $\mathcal{U}$ of $n$ elements and a collection $\mathcal{S}$ of $k$ subsets of $\mathcal{U}$. Moreover, a cost function is associated with each set. The goal is to…

Data Structures and Algorithms · Computer Science 2026-05-29 Michał Szyfelbein

We consider the problem of minimizing the total processing time of tardy jobs on a single machine. This is a classical scheduling problem, first considered by [Lawler and Moore 1969], that also generalizes the Subset Sum problem. Recently,…

Data Structures and Algorithms · Computer Science 2023-01-18 Baruch Schieber , Pranav Sitaraman

We give the first polynomial-time approximation scheme (PTAS) for the stochastic load balancing problem when the job sizes follow Poisson distributions. This improves upon the 2-approximation algorithm due to Goel and Indyk (FOCS'99).…

Data Structures and Algorithms · Computer Science 2020-06-24 Anindya De , Sanjeev Khanna , Huan Li , Hesam Nikpey

The starting point of this paper is the problem of scheduling $n$ jobs with processing times and due dates on a single machine so as to minimize the total processing time of tardy jobs, i.e., $1||\sum p_j U_j$. This problem was identified…

Data Structures and Algorithms · Computer Science 2022-11-11 Kim-Manuel Klein , Adam Polak , Lars Rohwedder

In this paper, we propose a general framework to design {efficient} polynomial time approximation schemes (EPTAS) for fundamental stochastic combinatorial optimization problems. Given an error parameter $\epsilon>0$, such algorithmic…

Data Structures and Algorithms · Computer Science 2025-05-30 Danny Segev , Sahil Singla

Arising from structural graph theory, treewidth has become a focus of study in fixed-parameter tractable algorithms in various communities including combinatorics, integer-linear programming, and numerical analysis. Many NP-hard problems…

Data Structures and Algorithms · Computer Science 2023-09-14 Sally Dong , Yin Tat Lee , Guanghao Ye

Scheduling on related machines ($Q||C_{\max}$) is one of the most important problems in the field of Algorithmic Mechanism Design. Each machine is controlled by a selfish agent and her valuation can be expressed via a single parameter, her…

Computer Science and Game Theory · Computer Science 2009-07-20 George Christodoulou , Annamaria Kovacs

We give a deterministic, polynomial-time algorithm for approximately counting the number of {0,1}-solutions to any instance of the knapsack problem. On an instance of length n with total weight W and accuracy parameter eps, our algorithm…

Data Structures and Algorithms · Computer Science 2010-08-20 Parikshit Gopalan , Adam Klivans , Raghu Meka

Pareto optimization via evolutionary multi-objective algorithms has been shown to efficiently solve constrained monotone submodular functions. Traditionally when solving multiple problems, the algorithm is run for each problem separately.…

Neural and Evolutionary Computing · Computer Science 2026-04-17 Liam Wigney , Frank Neumann
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