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We study the fundamental problem of sampling independent events, called subset sampling. Specifically, consider a set of $n$ events $S=\{x_1, \ldots, x_n\}$, where each event $x_i$ has an associated probability $p(x_i)$. The subset sampling…

Data Structures and Algorithms · Computer Science 2023-09-22 Lu Yi , Hanzhi Wang , Zhewei Wei

In this paper, we study the following problem: given $n$ subsets $S_1, \dots, S_n$ of an integer universe $U = \{0,\dots, u-1\}$, having total cardinality $N = \sum_{i=1}^n |S_i|$, find a prefix-free encoding $enc : U \rightarrow \{0,1\}^+$…

Data Structures and Algorithms · Computer Science 2025-04-16 Jarno N. Alanko , Ruben Becker , Davide Cenzato , Travis Gagie , Sung-Hwan Kim , Bojana Kodric , Nicola Prezza

We introduce and study a novel generalization of the classical Knapsack Problem (KP), called the Colored Knapsack Problem (CKP). In this problem, the items are partitioned into classes of colors and the packed items need to be ordered such…

Optimization and Control · Mathematics 2026-02-13 Fabio Ciccarelli , Alexander Helber , Erik Mühmer

Given two point sets $S$ and $T$, the minimum-cost many-to-many matching with demands (MMD) problem is the problem of finding a minimum-cost many-to-many matching between $S$ and $T$ such that each point of $S$ (respectively $T$) is matched…

Computational Geometry · Computer Science 2025-10-28 Fatemeh Rajabi-Alni , Behrouz Minaei-Bidgoli

In this paper, we investigate the parametric knapsack problem, in which the item profits are affine functions depending on a real-valued parameter. The aim is to provide a solution for all values of the parameter. It is well-known that any…

Data Structures and Algorithms · Computer Science 2017-01-30 Michael Holzhauser , Sven O. Krumke

Finding inclusion-minimal "hitting sets" for a given collection of sets is a fundamental combinatorial problem with applications in domains as diverse as Boolean algebra, computational biology, and data mining. Much of the algorithmic…

Data Structures and Algorithms · Computer Science 2016-01-13 Andrew Gainer-Dewar , Paola Vera-Licona

Let $G$ be a graph, which represents a social network, and suppose each node $v$ has a threshold value $\tau(v)$. Consider an initial configuration, where each node is either positive or negative. In each discrete time step, a node $v$…

Data Structures and Algorithms · Computer Science 2023-07-19 Hossein Soltani , Ahad N. Zehmakan , Ataabak B. Hushmandi

Suppose we are given a set of t coins which look identical, but a known number s of them are counterfeit, with a known weight different from the others. Our problem is to locate the counterfeits by weighing subsets of the t coins, with as…

Combinatorics · Mathematics 2007-05-23 Shaohui Zhai

Order picking is the problem of collecting a set of products in a warehouse in a minimum amount of time. It is currently a major bottleneck in supply-chain because of its cost in time and labor force. This article presents two exact and…

Data Structures and Algorithms · Computer Science 2018-06-05 Lucie Pansart , Nicolas Catusse , Hadrien Cambazard

We revisit the 3SUM problem in the \emph{preprocessed universes} setting. We present an algorithm that, given three sets $A$, $B$, $C$ of $n$ integers, preprocesses them in quadratic time, so that given any subsets $A' \subseteq A$, $B'…

Data Structures and Algorithms · Computer Science 2025-10-22 Shashwat Kasliwal , Adam Polak , Pratyush Sharma

M.Alekhnovich et al. recently have proposed a model of algorithms, called BT model, which covers Greedy, Backtrack and Simple Dynamic Programming methods and can be further divided into fixed, adaptive and fully adaptive three kinds, and…

Computational Complexity · Computer Science 2007-05-23 Xin Li , Tian Liu , Han Peng , Hongtao Sun , Jiaqi Zhu

We present new exact and approximation algorithms for 0-1-Knapsack and Unbounded Knapsack: * Exact Algorithm for 0-1-Knapsack: 0-1-Knapsack has known algorithms running in time $\widetilde{O}(n + \min\{n OPT, n W, OPT^2, W^2\})$, where $n$…

Data Structures and Algorithms · Computer Science 2022-05-18 Karl Bringmann , Alejandro Cassis

Despite the significant interest and progress in reinforcement learning (RL) problems with adversarial corruption, current works are either confined to the linear setting or lead to an undesired $\tilde{O}(\sqrt{T}\zeta)$ regret bound,…

Machine Learning · Statistics 2024-02-13 Chenlu Ye , Wei Xiong , Quanquan Gu , Tong Zhang

We study the weighted token swapping problem, in which we are given a graph on $n$ vertices, $n$ weighted tokens, an initial assignment of one token to each vertex, and a final assignment of one token to each vertex. The goal is to find a…

Data Structures and Algorithms · Computer Science 2025-08-01 Nicole Wein , Guanyu Tony Zhang

Parallel machine scheduling has been extensively studied in the past decades, with applications ranging from production planning to job processing in large computing clusters. In this work we study some of these fundamental optimization…

Data Structures and Algorithms · Computer Science 2015-09-08 Yael Mordechai

What is the minimal information that a robot must retain to achieve its task? To design economical robots, the literature dealing with reduction of combinatorial filters approaches this problem algorithmically. As lossless state compression…

Robotics · Computer Science 2024-10-15 Yulin Zhang , Dylan A. Shell

We present algorithms for the Max-Cover and Max-Unique-Cover problems in the data stream model. The input to both problems are $m$ subsets of a universe of size $n$ and a value $k\in [m]$. In Max-Cover, the problem is to find a collection…

Data Structures and Algorithms · Computer Science 2021-02-18 Andrew McGregor , David Tench , Hoa T. Vu

Pruhs and Woeginger prove the existence of FPTAS's for a general class of minimization and maximization subset selection problems. Without losing generality from the original framework, we prove how better asymptotic worst-case running…

Computational Complexity · Computer Science 2016-07-28 Cédric Bentz , Pierre Le Bodic

This paper leverages machine-learned predictions to design competitive algorithms for online conversion problems with the goal of improving the competitive ratio when predictions are accurate (i.e., consistency), while also guaranteeing a…

Machine Learning · Computer Science 2021-09-06 Bo Sun , Russell Lee , Mohammad Hajiesmaili , Adam Wierman , Danny H. K. Tsang

In this work we revisit the elementary scheduling problem $1||\sum p_j U_j$. The goal is to select, among $n$ jobs with processing times and due dates, a subset of jobs with maximum total processing time that can be scheduled in sequence…

Data Structures and Algorithms · Computer Science 2025-07-23 Nick Fischer , Leo Wennmann
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