A sample implementation for parallelizing Divide-and-Conquer algorithms on the GPU [PDF]
Heliyon, 2018 The strategy of Divide-and-Conquer (D&C) is one of the frequently used programming patterns to design efficient algorithms in computer science, which has been parallelized on shared memory systems and distributed memory systems.
Gang Mei +3 more
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Hybrid divide-and-conquer approach for tree search algorithms [PDF]
Quantum, 2023 One of the challenges of quantum computers in the near- and mid- term is the limited number of qubits we can use for computations. Finding methods that achieve useful quantum improvements under size limitations is thus a key question in the field.
Mathys Rennela +3 more
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A divide-and-conquer algorithm for large-scale de novo transcriptome assembly through combining small assemblies from existing algorithms [PDF]
BMC Genomics, 2017 Background While the continued development of high-throughput sequencing has facilitated studies of entire transcriptomes in non-model organisms, the incorporation of an increasing amount of RNA-Seq libraries has made de novo transcriptome assembly ...
Sing-Hoi Sze +2 more
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A distributed algorithm for solving large-scale p-median problems using expectation maximization [PDF]
PeerJ Computer ScienceThe p-median problem selects p source locations to serve n destinations such that the average distance between the destinations and corresponding sources is minimized.
Harsha Gwalani +4 more
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Application and assessment of divide-and-conquer-based heuristic algorithms for some integer optimization problems [PDF]
Yugoslav Journal of Operations Research, 2023 In this paper three heuristic algorithms using the Divide-and-Conquer paradigm are developed and assessed for three integer optimizations problems: Multidimensional Knapsack Problem (d-KP), Bin Packing Problem (BPP) and Travelling Salesman Problem (TSP).
Morales Fernando A.
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A scalable association rule learning heuristic for large datasets
Journal of Big Data, 2021 Many algorithms have proposed to solve the association rule learning problem. However, most of these algorithms suffer from the problem of scalability either because of tremendous time complexity or memory usage, especially when the dataset is large and ...
Haosong Li, Phillip C.-Y. Sheu
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Polynomial tails of additive-type recursions [PDF]
Discrete Mathematics & Theoretical Computer Science, 2008 Polynomial bounds and tail estimates are derived for additive random recursive sequences, which typically arise as functionals of recursive structures, of random trees, or in recursive algorithms.
Eva-Maria Schopp
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Maximum Correntropy Criterion with Distributed Method
Mathematics, 2022 The Maximum Correntropy Criterion (MCC) has recently triggered enormous research activities in engineering and machine learning communities since it is robust when faced with heavy-tailed noise or outliers in practice.
Fan Xie +3 more
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A Parallel Divide-and-Conquer-Based Evolutionary Algorithm for Large-Scale Optimization
IEEE Access, 2019 Large-scale optimization problems that involve thousands of decision variables have extensively arisen from various industrial areas. As a powerful optimization tool for many real-world applications, evolutionary algorithms (EAs) fail to solve the ...
Peng Yang, Ke Tang, Xin Yao
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Fast divide-and-conquer algorithms for preemptive scheduling problems with controllable processing times – A polymatroid optimization approach [PDF]
, 2008 We consider a variety of preemptive scheduling problems with controllable processing times on a single machine and on identical/uniform parallel machines, where the objective is to minimize the total compression cost.
A. Federgruen +20 more
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