Constructing Linear-Sized Spectral Sparsification in Almost-Linear Time
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Abstract (arXiv)
We present the first almost-linear time algorithm for constructing linear-sized spectral sparsification for graphs. This improves all previous constructions of linear-sized spectral sparsification, which requires Omega(n2) time. A key ingredient in our algorithm is a novel combination of two techniques used in literature for constructing spectral sparsification: Random sampling by effective resistance, and adaptive constructions based on barrier functions.
Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Aug 2015.
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Citing papers per year: 2021: 3; 2022: 3; 2023: 3; 2024: 5; 2025: 3.
17 papers.
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- 2024A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensationcited by 57
- 2021Graph Coarsening with Neural Networkscited by 55
- 2024Graph Coarsening with Message-Passing Guaranteescited by 9
- 2021A Generic Graph Sparsification Framework using Deep Reinforcement Learningcited by 8
- 2024Optimal sampling for least-squares approximationcited by 6
- 2025Large-Scale Spectral Graph Neural Networks via Laplacian Sparsification: Technical Reportcited by 5
- 2023Query Complexity of Active Learning for Function Family With Nearly Orthogonal Basiscited by 4
- 2022Sparsification of Decomposable Submodular Functionscited by 3
- 2023Fast Approximation of Similarity Graphs with Kernel Density Estimationcited by 3
- 2024Robust Offline Active Learning on Graphscited by 3
- 2025Taxonomy of reduction matrices for Graph Coarseningcited by 3
- 2022Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimationcited by 2
5 more
- 2022Sparsification of the regularized magnetic Laplacian with multi-type spanning forestscited by 1
- 2021Semi-supervised Active Regressioncited by 0
- 2023PRIMO: Private Regression in Multiple Outcomescited by 0
- 2024Almost linear time differentially private release of synthetic graphscited by 0
- 2025Online Sparsification of Bipartite-Like Clusters in Graphscited by 0
- 2025Online Sparsification of Bipartite-Like Clusters in Graphs7 Aug 2025
- 2025Taxonomy of reduction matrices for Graph Coarsening13 Jun 2025
- 2025Large-Scale Spectral Graph Neural Networks via Laplacian Sparsification: Technical Report8 Jan 2025
- 2024Optimal sampling for least-squares approximation4 Sep 2024
- 2024Robust Offline Active Learning on Graphs15 Aug 2024
- 2024Almost linear time differentially private release of synthetic graphs4 Jun 2024
- 2024Graph Coarsening with Message-Passing Guarantees28 May 2024
- 2024A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation29 Jan 2024
- 2023Fast Approximation of Similarity Graphs with Kernel Density Estimation21 Oct 2023
- 2023Query Complexity of Active Learning for Function Family With Nearly Orthogonal Basis6 Jun 2023
- 2023PRIMO: Private Regression in Multiple Outcomes7 Mar 2023
- 2022Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation1 Dec 2022
5 more
- 2022Sparsification of the regularized magnetic Laplacian with multi-type spanning forests31 Aug 2022
- 2022Sparsification of Decomposable Submodular Functions18 Jan 2022
- 2021A Generic Graph Sparsification Framework using Deep Reinforcement Learning2 Dec 2021
- 2021Semi-supervised Active Regression12 Jun 2021
- 2021Graph Coarsening with Neural Networks2 Feb 2021
- 2024A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensationcited by 57
- 2021Graph Coarsening with Neural Networkscited by 55
- 2024Graph Coarsening with Message-Passing Guaranteescited by 9
- 2021A Generic Graph Sparsification Framework using Deep Reinforcement Learningcited by 8
- 2024Optimal sampling for least-squares approximationcited by 6
- 2025Large-Scale Spectral Graph Neural Networks via Laplacian Sparsification: Technical Reportcited by 5
- 2023Query Complexity of Active Learning for Function Family With Nearly Orthogonal Basiscited by 4
- 2022Sparsification of Decomposable Submodular Functionscited by 3
- 2023Fast Approximation of Similarity Graphs with Kernel Density Estimationcited by 3
- 2024Robust Offline Active Learning on Graphscited by 3
- 2025Taxonomy of reduction matrices for Graph Coarseningcited by 3
- 2022Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimationcited by 2
12 most cited of 17 All 17 (JSON)
- 2025Online Sparsification of Bipartite-Like Clusters in Graphs7 Aug 2025
- 2025Taxonomy of reduction matrices for Graph Coarsening13 Jun 2025
- 2025Large-Scale Spectral Graph Neural Networks via Laplacian Sparsification: Technical Report8 Jan 2025
- 2024Optimal sampling for least-squares approximation4 Sep 2024
- 2024Robust Offline Active Learning on Graphs15 Aug 2024
- 2024Almost linear time differentially private release of synthetic graphs4 Jun 2024
- 2024Graph Coarsening with Message-Passing Guarantees28 May 2024
- 2024A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation29 Jan 2024
- 2023Fast Approximation of Similarity Graphs with Kernel Density Estimation21 Oct 2023
- 2023Query Complexity of Active Learning for Function Family With Nearly Orthogonal Basis6 Jun 2023
- 2023PRIMO: Private Regression in Multiple Outcomes7 Mar 2023
- 2022Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation1 Dec 2022
12 newest of 17 All 17 (JSON)