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Related papers: Round Compression for Parallel Matching Algorithms

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In this paper we study MapReduce computations from a complexity-theoretic perspective. First, we formulate a uniform version of the MRC model of Karloff et al. (2010). We then show that the class of regular languages, and moreover all of…

Computational Complexity · Computer Science 2015-10-07 Benjamin Fish , Jeremy Kun , Ádám Dániel Lelkes , Lev Reyzin , György Turán

In this paper, we study the MapReduce framework from an algorithmic standpoint and demonstrate the usefulness of our approach by designing and analyzing efficient MapReduce algorithms for fundamental sorting, searching, and simulation…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-01-11 Michael T. Goodrich , Nodari Sitchinava , Qin Zhang

A fundamental problem in shape matching and geometric similarity is computing the maximum area overlap between two polygons under translation. For general simple polygons, the best-known algorithm runs in $O((nm)^2 \log(nm))$ time [Mount,…

Computational Geometry · Computer Science 2025-11-07 Mikkel Abrahamsen , Sujoy Bhore , Maike Buchin , Jacobus Conradi , Ce Jin , André Nusser , Carolin Rehs

We show that a simple algorithm for computing a matching on a graph runs in a logarithmic number of phases incurring work linear in the input size. The algorithm can be adapted to provide efficient algorithms in several models of…

Data Structures and Algorithms · Computer Science 2014-02-04 Marcel Birn , Vitaly Osipov , Peter Sanders , Christian Schulz , Nodari Sitchinava

This paper initiates the study of I/O algorithms (minimizing cache misses) from the perspective of fine-grained complexity (conditional polynomial lower bounds). Specifically, we aim to answer why sparse graph problems are so hard, and why…

Data Structures and Algorithms · Computer Science 2017-12-06 Erik D. Demaine , Andrea Lincoln , Quanquan C. Liu , Jayson Lynch , Virginia Vassilevska Williams

Maximal Clique Enumeration (MCE) is a fundamental graph mining problem, and is useful as a primitive in identifying dense structures in a graph. Due to the high computational cost of MCE, parallel methods are imperative for dealing with…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-31 Apurba Das , Seyed-Vahid Sanei-Mehri , Srikanta Tirthapura

We revisit the simultaneous approximation model for the correlation clustering problem introduced by Davies, Moseley, and Newman[DMN24]. The objective is to find a clustering that minimizes given norms of the disagreement vector over all…

Data Structures and Algorithms · Computer Science 2024-10-23 Nairen Cao , Shi Li , Jia Ye

We pursue a study of the Generalized Demand Matching problem, a common generalization of the $b$-Matching and Knapsack problems. Here, we are given a graph with vertex capacities, edge profits, and asymmetric demands on the edges. The goal…

Data Structures and Algorithms · Computer Science 2017-05-31 Sara Ahmadian , Zachary Friggstad

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

We provide a simple new randomized contraction approach to the global minimum cut problem for simple undirected graphs. The contractions exploit 2-out edge sampling from each vertex rather than the standard uniform edge sampling. We…

Data Structures and Algorithms · Computer Science 2019-09-04 Mohsen Ghaffari , Krzysztof Nowicki , Mikkel Thorup

In the \textsc{Maximum Degree Contraction} problem, input is a graph $G$ on $n$ vertices, and integers $k, d$, and the objective is to check whether $G$ can be transformed into a graph of maximum degree at most $d$, using at most $k$ edge…

Data Structures and Algorithms · Computer Science 2020-09-25 Saket Saurabh , Prafullkumar Tale

Graph clustering has many important applications in computing, but due to growing sizes of graphs, even traditionally fast clustering methods such as spectral partitioning can be computationally expensive for real-world graphs of interest.…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-11 Julian Shun , Farbod Roosta-Khorasani , Kimon Fountoulakis , Michael W. Mahoney

Mixed packing and covering problems are problems that can be formulated as linear programs using only non-negative coefficients. Examples include multicommodity network flow, the Held-Karp lower bound on TSP, fractional relaxations of set…

Data Structures and Algorithms · Computer Science 2016-01-19 Neal E. Young

We study the parallel complexity of finding a basis of a graphic matroid under independence-oracle access. Karp, Upfal, and Wigderson (FOCS 1985, JCSS 1988) initiated the study of this problem and established two algorithms for finding a…

Data Structures and Algorithms · Computer Science 2025-11-10 Sanjeev Khanna , Aaron Putterman , Junkai Song

To design efficient parallel algorithms, some recent papers showed that many sequential iterative algorithms can be directly parallelized but there are still challenges in achieving work-efficiency and high-parallelism. Work-efficiency can…

Data Structures and Algorithms · Computer Science 2022-05-27 Zheqi Shen , Zijin Wan , Yan Gu , Yihan Sun

Data structures that allow efficient distance estimation (distance oracles, distance sketches, etc.) have been extensively studied, and are particularly well studied in centralized models and classical distributed models such as CONGEST. We…

Data Structures and Algorithms · Computer Science 2019-09-13 Michael Dinitz , Yasamin Nazari

In the semi-streaming model for processing massive graphs, an algorithm makes multiple passes over the edges of a given $n$-vertex graph and is tasked with computing the solution to a problem using $O(n \cdot \text{polylog}(n))$ space.…

Data Structures and Algorithms · Computer Science 2023-12-21 Sepehr Assadi , Christian Konrad , Kheeran K. Naidu , Janani Sundaresan

Supercomputers are equipped with an increasingly large number of cores to use computational power as a way of solving problems that are otherwise intractable. Unfortunately, getting serial algorithms to run in parallel to take advantage of…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-12-31 Faisal N. Abu-Khzam , Khuzaima Daudjee , Amer E. Mouawad , Naomi Nishimura

In this paper, a fully compressed pattern matching problem is studied. The compression is represented by straight-line programs (SLPs), i.e. a context-free grammars generating exactly one string; the term fully means that both the pattern…

Data Structures and Algorithms · Computer Science 2013-06-26 Artur Jeż

Given two algorithms for the same problem, can we determine whether they are meaningfully different? In full generality, the question is uncomputable, and empirically it is muddied by competing notions of similarity. Yet, in many…

Machine Learning · Computer Science 2025-11-03 Shairoz Sohail , Taher Ali
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