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The goal of this paper is to understand how exponential-time approximation algorithms can be obtained from existing polynomial-time approximation algorithms, existing parameterized exact algorithms, and existing parameterized approximation…

Data Structures and Algorithms · Computer Science 2023-06-28 Barış Can Esmer , Ariel Kulik , Dániel Marx , Daniel Neuen , Roohani Sharma

The Traveling Thief Problem (TTP) is a multi-component optimization problem that captures the interplay between routing and packing decisions by combining the classical Traveling Salesperson Problem (TSP) and the Knapsack Problem (KP). The…

Data Structures and Algorithms · Computer Science 2026-04-22 Jan Eube , Kelin Luo , Aneta Neumann , Frank Neumann , Heiko Röglin

The Erd\H{o}s-Ginzburg-Ziv theorem states that every sequence of 2n - 1 integers contains a subsequence of length n whose sum is divisible by n. Choi, Kang, and Lim gave a simple deterministic O(n log n) algorithm for finding such a…

Data Structures and Algorithms · Computer Science 2026-05-22 Sunghyeon Jo

We present a new approach for finding matchings in dense graphs by building on Szemer\'edi's celebrated Regularity Lemma. This allows us to obtain non-trivial albeit slight improvements over longstanding bounds for matchings in streaming…

Data Structures and Algorithms · Computer Science 2022-07-20 Sepehr Assadi , Soheil Behnezhad , Sanjeev Khanna , Huan Li

A maximal matching can be maintained in fully dynamic (supporting both addition and deletion of edges) $n$-vertex graphs using a trivial deterministic algorithm with a worst-case update time of O(n). No deterministic algorithm that…

Data Structures and Algorithms · Computer Science 2013-02-19 Ofer Neiman , Shay Solomon

Assume that a target is known to be present at an unknown point among a finite set of locations in the plane. We search for it using a mobile robot that has imperfect sensing capabilities. It takes time for the robot to move between…

We consider global optimization problems, where the feasible region $\X$ is a compact subset of $\mathbb{R}^d$ with $d \geq 10$. For these problems, we demonstrate the following. First: the actual convergence of global random search…

Optimization and Control · Mathematics 2023-02-27 Jack Noonan , Anatoly Zhigljavsky

This paper proposes an analytical framework for modelling resource contention in multi-robot systems, where the travel times and task durations are uncertain. It uses several approximation methods to quickly and accurately calculate the…

Multiagent Systems · Computer Science 2020-03-17 Andrew W. Palmer , Andrew J. Hill , Steven J. Scheding

We consider the problem of searching for an object on a line at an unknown distance OPT from the original position of the searcher, in the presence of a cost of d for each time the searcher changes direction. This is a generalization of the…

Data Structures and Algorithms · Computer Science 2007-05-23 Erik D. Demaine , Sandor P. Fekete , Shmuel Gal

Thirty years ago, the Robin Hood collision resolution strategy was introduced for open addressing hash tables, and a recurrence equation was found for the distribution of its search cost. Although this recurrence could not be solved…

Data Structures and Algorithms · Computer Science 2016-05-16 Patricio V. Poblete , Alfredo Viola

We present a deterministic $(1+o(1))$-approximation $(n^{1/2+o(1)}+D^{1+o(1)})$-time algorithm for solving the single-source shortest paths problem on distributed weighted networks (the CONGEST model); here $n$ is the number of nodes in the…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-09-20 Monika Henzinger , Sebastian Krinninger , Danupon Nanongkai

A recently discovered universal rank-based matrix method to extract trends from noisy time series is described in [1] but the formula for the output matrix elements, implemented there as an open-access supplement MATLAB computer code, is…

Data Analysis, Statistics and Probability · Physics 2020-06-24 D. J. Kestner , G. R. Ierley , A. B. Kostinski

Routing problems such as Hamiltonian Path Problem (HPP), seeks a path to visit all the vertices in a graph while minimizing the path cost. This paper studies a variant, HPP with Probabilistic Terminals (HPP-PT), where each vertex has a…

Robotics · Computer Science 2026-01-21 Yunpeng Lyu , Chao Cao , Ji Zhang , Howie Choset , Zhongqiang Ren

In this paper, we study the problem of map matching with travel time constraints. Given a sequence of $k$ spatio-temporal measurements and an embedded path graph with travel time costs, the goal is to snap each measurement to a close-by…

Computational Geometry · Computer Science 2025-06-24 Yannick Bosch , Sabine Storandt

In the typical model, a discrete-time coined quantum walk searching the 2D grid for a marked vertex achieves a success probability of $O(1/\log N)$ in $O(\sqrt{N \log N})$ steps, which with amplitude amplification yields an overall runtime…

Quantum Physics · Physics 2018-02-15 Thomas G. Wong

In numerous online selection problems, decision-makers (DMs) must allocate on the fly limited resources to customers with uncertain values. The DM faces the tension between allocating resources to currently observed values and saving them…

Computer Science and Game Theory · Computer Science 2025-11-04 Yihua Xu , Süleyman Kerimov , Sebastian Perez-Salazar

We investigate the problem of finding a static treasure in anonymous graphs using oblivious agents and introduce a novel approach that leverages quantum information. In anonymous graphs, vertices are unlabelled, indistinguishable, and edges…

Quantum Physics · Physics 2025-09-04 Gaurav Gaur , Barun Gorain , Rishi Ranjan Singh , Daya Gaur

An attractor decomposition meta-algorithm for solving parity games is given that generalises the classic McNaughton-Zielonka algorithm and its recent quasi-polynomial variants due to Parys (2019), and to Lehtinen, Schewe, and Wojtczak…

Data Structures and Algorithms · Computer Science 2022-08-30 Marcin Jurdziński , Rémi Morvan , K. S. Thejaswini

Model-free continuous control for robot navigation tasks using Deep Reinforcement Learning (DRL) that relies on noisy policies for exploration is sensitive to the density of rewards. In practice, robots are usually deployed in cluttered…

Robotics · Computer Science 2023-02-24 Mingyu Cai , Erfan Aasi , Calin Belta , Cristian-Ioan Vasile

We present a Monte Carlo algorithm for Hamiltonicity detection in an $n$-vertex undirected graph running in $O^*(1.657^{n})$ time. To the best of our knowledge, this is the first superpolynomial improvement on the worst case runtime for the…

Data Structures and Algorithms · Computer Science 2010-08-04 Andreas Björklund
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