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Given a collection of $m$ sets from a universe $\mathcal{U}$, the Maximum Set Coverage problem consists of finding $k$ sets whose union has largest cardinality. This problem is NP-Hard, but the solution can be approximated by a polynomial…

Data Structures and Algorithms · Computer Science 2023-12-13 Stephen Jaud , Anthony Wirth , Farhana Choudhury

In this work, we consider the Submodular Maximization under Knapsack (SMK) constraint problem over the ground set of size $n$. The problem recently attracted a lot of attention due to its applications in various domains of combination…

Data Structures and Algorithms · Computer Science 2024-05-22 Canh V. Pham

We investigate pseudo-polynomial time algorithms for Subset Sum. Given a multi-set $X$ of $n$ positive integers and a target $t$, Subset Sum asks whether some subset of $X$ sums to $t$. Bringmann proposes an $\tilde{O}(n + t)$-time…

Data Structures and Algorithms · Computer Science 2026-04-29 Lin Chen , Jiayi Lian , Yuchen Mao , Guochuan Zhang

We reexamine the classical subset sum problem: given a set $X$ of $n$ positive integers and a number $t$, decide whether there exists a subset of $X$ that sums to $t$; or more generally, compute the set $\mbox{out}$ of all numbers…

Data Structures and Algorithms · Computer Science 2026-01-06 Timothy M. Chan

Given a multiset $X=\{x_1,..., x_n\}$ of real numbers, the {\it floating-point set summation} problem asks for $S_n=x_1+...+x_n$. Let $E^*_n$ denote the minimum worst-case error over all possible orderings of evaluating $S_n$. We prove that…

Data Structures and Algorithms · Computer Science 2024-09-21 Ming-Yang Kao , Jie Wang

The generalized egg dropping problem is a classic challenge in sequential decision-making. Standard dynamic programming evaluates the minimax minimum number of tests in $\mathcal{O}(K \cdot N^2)$ time. A known approach formulates the…

Data Structures and Algorithms · Computer Science 2026-05-18 Kleitos Papadopoulos

We investigate the classic Knapsack problem and propose a fully polynomial-time approximation scheme (FPTAS) that runs in $\widetilde{O}(n + (1/\varepsilon)^2)$ time. This improves upon the $\widetilde{O}(n + (1/\varepsilon)^{11/5})$-time…

Data Structures and Algorithms · Computer Science 2025-01-08 Lin Chen , Jiayi Lian , Yuchen Mao , Guochuan Zhang

We consider the SUBSET SUM problem and its important variants in this paper. In the SUBSET SUM problem, a (multi-)set $X$ of $n$ positive numbers and a target number $t$ are given, and the task is to find a subset of $X$ with the maximal…

Data Structures and Algorithms · Computer Science 2022-12-07 Xiaoyu Wu , Lin Chen

We study the two-dimensional geometric knapsack problem for convex polygons. Given a set of weighted convex polygons and a square knapsack, the goal is to select the most profitable subset of the given polygons that fits non-overlappingly…

Data Structures and Algorithms · Computer Science 2020-08-03 Arturo Merino , Andreas Wiese

We consider the classic Facility Location, $k$-Median, and $k$-Means problems in metric spaces of doubling dimension $d$. We give nearly linear-time approximation schemes for each problem. The complexity of our algorithms is…

Data Structures and Algorithms · Computer Science 2020-05-21 Vincent Cohen-Addad , Andreas Emil Feldmann , David Saulpic

We investigate the question whether Subset Sum can be solved by a polynomial-time algorithm with access to a certificate of length poly(k) where k is the maximal number of bits in an input number. In other words, can it be solved using only…

Data Structures and Algorithms · Computer Science 2024-09-06 Michał Włodarczyk

We study the problem of maximizing a monotone submodular function subject to a Multiple Knapsack constraint. The input is a set $I$ of items, each has a non-negative weight, and a set of bins of arbitrary capacities. Also, we are given a…

Data Structures and Algorithms · Computer Science 2021-04-19 Yaron Fairstein , Ariel Kulik , Joseph , Naor , Danny Raz , Hadas Shachnai

In this work, we show the first worst-case to average-case reduction for the classical $k$-SUM problem. A $k$-SUM instance is a collection of $m$ integers, and the goal of the $k$-SUM problem is to find a subset of $k$ elements that sums to…

Computational Complexity · Computer Science 2020-11-12 Zvika Brakerski , Noah Stephens-Davidowitz , Vinod Vaikuntanathan

In the Max $r$-SAT problem, the input is a CNF formula with $n$ variables where each clause is a disjunction of at most $r$ literals. The objective is to compute an assignment which satisfies as many of the clauses as possible. While there…

Data Structures and Algorithms · Computer Science 2021-07-06 Arindam Biswas , Venkatesh Raman

Subset sum is a very old and fundamental problem in theoretical computer science. In this problem, $n$ items with weights $w_1, w_2, w_3, \ldots, w_n$ are given as input and the goal is to find out if there is a subset of them whose weights…

Data Structures and Algorithms · Computer Science 2022-09-13 Hamed Saleh , Saeed Seddighin

The subspace approximation problem Subspace($k$,$p$) asks for a $k$-dimensional linear subspace that fits a given set of points optimally, where the error for fitting is a generalization of the least squares fit and uses the $\ell_{p}$ norm…

Data Structures and Algorithms · Computer Science 2011-01-04 Amit Deshpande , Kasturi Varadarajan , Madhur Tulsiani , Nisheeth K. Vishnoi

We give efficient algorithms for volume sampling, i.e., for picking $k$-subsets of the rows of any given matrix with probabilities proportional to the squared volumes of the simplices defined by them and the origin (or the squared volumes…

Data Structures and Algorithms · Computer Science 2010-04-26 Amit Deshpande , Luis Rademacher

A constant-workspace algorithm has read-only access to an input array and may use only O(1) additional words of $O(\log n)$ bits, where $n$ is the size of the input. We assume that a simple $n$-gon is given by the ordered sequence of its…

Computational Geometry · Computer Science 2013-06-14 Tetsuo Asano , Kevin Buchin , Maike Buchin , Matias Korman , Wolfgang Mulzer , Günter Rote , André Schulz

We make progress on two important problems regarding attribute efficient learnability. First, we give an algorithm for learning decision lists of length $k$ over $n$ variables using $2^{\tilde{O}(k^{1/3})} \log n$ examples and time…

Machine Learning · Computer Science 2007-05-23 Adam R. Klivans , Rocco A. Servedio

While well-known methods to list the intersections of either a list of segments or a complex polygon aim at achieving optimal time-complexity they often do so at the cost of memory comsumption and complex code. Real-life software…

Computational Geometry · Computer Science 2013-05-28 Jean Souviron
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