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315,164
Analysis of multilevel graph partitioning
, 1995
"... Recently, a number of researchers have investigated a class of algorithms that are based on multilevel graph partitioning that have moderate computational complexity, and provide excellent graph partitions. However, there exists little theoretical analysis that could explain the ability of multileve ..."
Abstract

Cited by 107 (14 self)
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Recently, a number of researchers have investigated a class of algorithms that are based on multilevel graph partitioning that have moderate computational complexity, and provide excellent graph partitions. However, there exists little theoretical analysis that could explain the ability
Genetic Algorithms for Graph Partitioning and Incremental Graph Partitioning
 Proceedings of Supercomputing '94
, 1994
"... Partitioning graphs into equally large groups of nodes, minimizing the number of edges between different groups, is an extremely important problem in parallel computing. This paper presents genetic algorithms for suboptimal graph partitioning, with new crossover operators (KNUX, DKNUX) that lead to ..."
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Cited by 17 (6 self)
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Partitioning graphs into equally large groups of nodes, minimizing the number of edges between different groups, is an extremely important problem in parallel computing. This paper presents genetic algorithms for suboptimal graph partitioning, with new crossover operators (KNUX, DKNUX) that lead
Expander Flows, Geometric Embeddings and Graph Partitioning
 IN 36TH ANNUAL SYMPOSIUM ON THE THEORY OF COMPUTING
, 2004
"... We give a O( log n)approximation algorithm for sparsest cut, balanced separator, and graph conductance problems. This improves the O(log n)approximation of Leighton and Rao (1988). We use a wellknown semidefinite relaxation with triangle inequality constraints. Central to our analysis is a ..."
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Cited by 319 (18 self)
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We give a O( log n)approximation algorithm for sparsest cut, balanced separator, and graph conductance problems. This improves the O(log n)approximation of Leighton and Rao (1988). We use a wellknown semidefinite relaxation with triangle inequality constraints. Central to our analysis is a
Recent advances in graph partitioning
 Arxiv
"... Abstract. We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions. 1 ..."
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Cited by 5 (2 self)
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Abstract. We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions. 1
New Graph Partitioning Algorithms
, 1998
"... Graph partitioning problems are NPcomplete and various heuristic algorithms exist in the litterature. Particularly, spectral graph partitioning algorithms partition the graph using the eigenvector associated with the second smallest eigenvalue of the "graph Laplacian." Through the use of ..."
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Cited by 3 (2 self)
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Graph partitioning problems are NPcomplete and various heuristic algorithms exist in the litterature. Particularly, spectral graph partitioning algorithms partition the graph using the eigenvector associated with the second smallest eigenvalue of the "graph Laplacian." Through the use
Parallel Incremental Graph Partitioning
"... Partitioning graphs into equally large groups of nodes while minimizing the number of edges between different groups is an extremely important problem in parallel computing. For instance, efficiently parallelizing several scientific and engineering applications requires the partitioning of data or t ..."
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Cited by 22 (0 self)
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Partitioning graphs into equally large groups of nodes while minimizing the number of edges between different groups is an extremely important problem in parallel computing. For instance, efficiently parallelizing several scientific and engineering applications requires the partitioning of data
FENNEL: Streaming Graph Partitioning . . .
, 2012
"... ... efficient solving of a wide range of computational tasks and querying over largescale graph data, such as computing node centralities using iterative computations, and personalized recommendations. In this work, we introduce a unifying framework for graph partitioning which enables a well princ ..."
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... efficient solving of a wide range of computational tasks and querying over largescale graph data, such as computing node centralities using iterative computations, and personalized recommendations. In this work, we introduce a unifying framework for graph partitioning which enables a well
Multilevel Graph Partitioning Schemes
 Proc. 24th Intern. Conf. Par. Proc., III
, 1995
"... Abstract – In this paper we present experiments with a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, partition the smaller graph, and then uncoarsen it to construct a partition for the original graph. We investigate the effectiveness of ma ..."
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Cited by 40 (0 self)
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Abstract – In this paper we present experiments with a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, partition the smaller graph, and then uncoarsen it to construct a partition for the original graph. We investigate the effectiveness
NonUniform Graph Partitioning
"... We consider the problem of NONUNIFORM GRAPH PARTITIONING, where the input is an edgeweighted undirected graph G = (V, E) and k capacities n1,..., nk, and the goal is to find a partition {S1, S2,..., Sk} of V satisfying Sj  ≤ nj for all 1 ≤ j ≤ k, that minimizes the total weight of edges crossi ..."
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We consider the problem of NONUNIFORM GRAPH PARTITIONING, where the input is an edgeweighted undirected graph G = (V, E) and k capacities n1,..., nk, and the goal is to find a partition {S1, S2,..., Sk} of V satisfying Sj  ≤ nj for all 1 ≤ j ≤ k, that minimizes the total weight of edges
Results 1  10
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