Bipartite Matching in Nearly-linear Time on Moderately Dense Graphs
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Abstract (arXiv)
We present an tilde O(m+n1.5)-time randomized algorithm for maximum cardinality bipartite matching and related problems (e.g. transshipment, negative-weight shortest paths, and optimal transport) on m-edge, n-node graphs. For maximum cardinality bipartite matching on moderately dense graphs, i.e. m = Omega(n1.5), our algorithm runs in time nearly linear in the input size and constitutes the first improvement over the classic O(m√n)-time [Dinic 1970; Hopcroft-Karp 1971; Karzanov 1973] and tilde O(nω)-time algorithms [Ibarra-Moran 1981; Mucha-Sankowski 2004] (where currently ω≈ 2.373). On sparser graphs, i.e. when m = n9/8 + δ for any constant δ>0, our result improves upon the recent advances of [Madry 2013] and [Liu-Sidford 2020b, 2020a] which achieve an tilde O(m4/3+o(1)) runtime. We obtain these results by combining and advancing recent lines of research in interior point methods (IPMs) and dynamic graph algorithms. First, we simplify and improve the IPM of [v.d.Brand-Lee-Sidford-Song 2020], providing a general primal-dual IPM framework and new sampling-based techniques for handling infeasibility induced by approximate linear system solvers. Second, we provide a simple sublinear-time algorithm for detecting and sampling high-energy edges in electric flows on expanders and show that when combined with recent advances in dynamic expander decompositions, this yields efficient data structures for maintaining the iterates of both [v.d.Brand et al.] and our new IPMs. Combining this general machinery yields a simpler tilde O(n √m) time algorithm for matching based on the logarithmic barrier function, and our state-of-the-art tilde O(m+n1.5) time algorithm for matching based on the [Lee-Sidford 2014] barrier (as regularized in [v.d.Brand et al.]).
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Sep 2020.
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Citing papers per year: 2021: 3; 2022: 1; 2023: 2; 2024: 3; 2025: 1; 2026: 1.
11 papers.
- 2021Faster Matchings via Learned Dualscited by 56
- 2021Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structurescited by 19
- 2022Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictionscited by 16
- 2021Sublinear Least-Squares Value Iteration via Locality Sensitive Hashingcited by 15
- 2023A Whole New Ball Game: A Primal Accelerated Method for Matrix Games and Minimizing the Maximum of Smooth Functionscited by 3
- 2023Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methodscited by 2
- 2024Near-Optimal Algorithms for Constrained k-Center Clustering with Instance-level Background Knowledgecited by 2
- 2026Optimized Algorithms for Text Clustering with LLM-Generated Constraintscited by 2
- 2024Quantum Speedup for Spectral Approximation of Kronecker Productscited by 1
- 2024Binary Hypothesis Testing for Softmax Models and Leverage Score Modelscited by 1
- 2025Hierarchical Forecast Reconciliation on Networks: A Network Flow Optimization Formulationcited by 0
- 2026Optimized Algorithms for Text Clustering with LLM-Generated Constraints16 Jan 2026
- 2025Hierarchical Forecast Reconciliation on Networks: A Network Flow Optimization Formulation6 May 2025
- 2024Binary Hypothesis Testing for Softmax Models and Leverage Score Models9 May 2024
- 2024Quantum Speedup for Spectral Approximation of Kronecker Products10 Feb 2024
- 2024Near-Optimal Algorithms for Constrained k-Center Clustering with Instance-level Background Knowledge23 Jan 2024
- 2023A Whole New Ball Game: A Primal Accelerated Method for Matrix Games and Minimizing the Maximum of Smooth Functions17 Nov 2023
- 2023Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods30 Jan 2023
- 2022Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions20 May 2022
- 2021Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures30 Nov 2021
- 2021Faster Matchings via Learned Duals20 Jul 2021
- 2021Sublinear Least-Squares Value Iteration via Locality Sensitive Hashing18 May 2021