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Semi-online algorithms that are allowed to perform a bounded amount of repacking achieve guaranteed good worst-case behaviour in a more realistic setting. Most of the previous works focused on minimization problems that aim to minimize some…

Data Structures and Algorithms · Computer Science 2021-04-21 Sebastian Berndt , Kilian Grage , Klaus Jansen , Lukas Johannsen , Maria Kosche

We consider a variant of the knapsack problem, where items are available with different possible weights. Using a separate budget for these item improvements, the question is: Which items should be improved to which degree such that the…

Optimization and Control · Mathematics 2016-07-29 Marc Goerigk , Yogish Sabharwal , Anita Schöbel , Sandeep Sen

We consider the problem of finding a desired item out of $N$ items arranged on the sites of a two-dimensional lattice of size $\sqrt{N} \times \sqrt{N}$. The previous quantum walk based algorithms take $O(\sqrt{N}\log N)$ steps to solve…

Quantum Physics · Physics 2009-11-13 Avatar Tulsi

The Time-Invariant Incremental Knapsack problem (IIK) is a generalization of Maximum Knapsack to a discrete multi-period setting. At each time, capacity increases and items can be added, but not removed from the knapsack. The goal is to…

Data Structures and Algorithms · Computer Science 2018-01-31 Yuri Faenza , Igor Malinovic

The problem of P vs. NP is very serious, and solutions to the problem can help save lives. This article is an attempt at solving the problem using a computer algorithm. It is presented in a fashion that will hopefully allow for easy…

Data Structures and Algorithms · Computer Science 2015-03-19 Matt Groff

We first give an $\O(2^{n/3})$ quantum algorithm for the 0-1 Knapsack problem with $n$ variables. More generally, for 0-1 Integer Linear Programs with $n$ variables and $d$ inequalities we give an $\O(2^{n/3}n^d)$ quantum algorithm. For $d…

Quantum Physics · Physics 2016-09-08 V. Arvind , Rainer Schuler

In the past decade, many parameterized algorithms were developed for packing problems. Our goal is to obtain tradeoffs that improve the running times of these algorithms at the cost of computing approximate solutions. Consider a packing…

Data Structures and Algorithms · Computer Science 2015-05-05 Meirav Zehavi

Convolutional neural networks (CNNs) are currently state-of-the-art for various classification tasks, but are computationally expensive. Propagating through the convolutional layers is very slow, as each kernel in each layer must…

Neural and Evolutionary Computing · Computer Science 2016-01-27 Tyler Highlander , Andres Rodriguez

Chv\'{a}tal and Klincsek (1980) gave an $O(n^3)$-time algorithm for the problem of finding a maximum-cardinality convex subset of an arbitrary given set $P$ of $n$ points in the plane. This paper examines a generalization of the problem,…

Computational Geometry · Computer Science 2021-08-31 Stephane Durocher , J. Mark Keil , Saeed Mehrabi , Debajyoti Mondal

Obtaining strong linear relaxations of capacitated covering problems constitute a major technical challenge even for simple settings. For one of the most basic cases, the Knapsack-Cover (Min-Knapsack) problem, the relaxation based on…

Data Structures and Algorithms · Computer Science 2019-12-30 Andrés Fielbaum , Ignacio Morales , José Verschae

The most fundamental problem considered in algorithms for text processing is pattern matching: given a pattern $p$ of length $m$ and a text $t$ of length $n$, does $p$ occur in $t$? Multiple versions of this basic question have been…

Data Structures and Algorithms · Computer Science 2021-11-10 Moses Ganardi , Paweł Gawrychowski

Given a $k$-CNF formula and an integer $s$, we study algorithms that obtain $s$ solutions to the formula that are maximally dispersed. For $s=2$, the problem of computing the diameter of a $k$-CNF formula was initiated by Creszenzi and…

Computational Complexity · Computer Science 2025-06-04 Per Austrin , Ioana O. Bercea , Mayank Goswami , Nutan Limaye , Adarsh Srinivasan

We consider the problem of maximizing a monotone submodular function subject to a knapsack constraint. Our main contribution is an algorithm that achieves a nearly-optimal, $1 - 1/e - \epsilon$ approximation, using…

Data Structures and Algorithms · Computer Science 2018-11-20 Alina Ene , Huy L. Nguyen

Symmetric submodular maximization is an important class of combinatorial optimization problems, including MAX-CUT on graphs and hyper-graphs. The state-of-the-art algorithm for the problem over general constraints has an approximation ratio…

Data Structures and Algorithms · Computer Science 2024-06-21 Zongqi Wan , Jialin Zhang , Xiaoming Sun , Zhijie Zhang

The Boolean constraint satisfaction problem 3-SAT is arguably the canonical NP-complete problem. In contrast, 2-SAT can not only be decided in polynomial time, but in fact in deterministic linear time. In 2006, Bravyi proposed a physically…

Quantum Physics · Physics 2016-10-25 Niel de Beaudrap , Sevag Gharibian

For any given $\epsilon>0$ we provide an algorithm for the Densest $k$-Subhypergraph Problem with an approximation ratio of at most $O(n^{\theta_m+2\epsilon})$ for $\theta_m=\frac{1}{2}m-\frac{1}{2}-\frac{1}{2m}$ and run time at most…

Data Structures and Algorithms · Computer Science 2016-10-18 Richard Taylor

We consider the problem of computing the Boolean convolution (with wraparound) of $n$~vectors of dimension $m$, or, equivalently, the problem of computing the sumset $A_1+A_2+\ldots+A_n$ for $A_1,\ldots,A_n \subseteq \mathbb{Z}_m$. Boolean…

Data Structures and Algorithms · Computer Science 2021-05-11 Karl Bringmann , Vasileios Nakos

In the Maximum Independent Set of Objects problem, we are given an $n$-vertex planar graph $G$ and a family $\mathcal{D}$ of $N$ objects, where each object is a connected subgraph of $G$. The task is to find a subfamily $\mathcal{F}…

Computational Geometry · Computer Science 2023-11-01 Jana Cslovjecsek , Michał Pilipczuk , Karol Węgrzycki

Many combinatorial problems involving weights can be formulated as a so-called ranged problem. That is, their input consists of a universe $U$, a (succinctly-represented) set family $\mathcal{F} \subseteq 2^{U}$, a weight function $\omega:U…

Data Structures and Algorithms · Computer Science 2012-08-22 Jesper Nederlof , Erik Jan van Leeuwen , Ruben van der Zwaan

The $1 \mid \mid \Sigma w_j U_j$ problem asks to determine -- given $n$ jobs each with its own processing time, weight, and due date -- the minimum weighted number of tardy jobs in any single machine non-preemptive schedule for these jobs.…

Data Structures and Algorithms · Computer Science 2022-09-12 Danny Hermelin , Hendrik Molter , Dvir Shabtay