Approximation algorithm for the balanced 2-correlation clustering problem on well-proportional graphs
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Publication:2039649
DOI10.1007/978-3-030-57602-8_9zbMath1482.68176OpenAlexW3047638929MaRDI QIDQ2039649
Sai Ji, Ling Gai, Dong-lei Du, Da-Chuan Xu
Publication date: 5 July 2021
Full work available at URL: https://doi.org/10.1007/978-3-030-57602-8_9
Graph theory (including graph drawing) in computer science (68R10) Edge subsets with special properties (factorization, matching, partitioning, covering and packing, etc.) (05C70) Approximation algorithms (68W25)
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Cites Work
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- Improved approximation algorithms for MAX \(k\)-cut and MAX BISECTION
- Correlation clustering
- Cluster graph modification problems
- Correlation clustering in data streams
- Correlation clustering in general weighted graphs
- Clustering with qualitative information
- Near Optimal LP Rounding Algorithm for CorrelationClustering on Complete and Complete k-partite Graphs
- Correlation Clustering with Constrained Cluster Sizes and Extended Weights Bounds
- Approximation Algorithms for Min-Sum k-Clustering and Balanced k-Median
- Correlation clustering with a fixed number of clusters
- Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
- Clustering Problems on Sliding Windows
- A Streaming Algorithm for k-Means with Approximate Coreset
- Improved Approximation Algorithms for Bipartite Correlation Clustering
- On Uniform Capacitated k -Median Beyond the Natural LP Relaxation
- Better Guarantees for $k$-Means and Euclidean $k$-Median by Primal-Dual Algorithms
- Convergence of Type-Symmetric and Cut-Balanced Consensus Seeking Systems
- Bi-Factor Approximation Algorithms for Hard Capacitated k-Median Problems
- Correlation Clustering and Biclustering With Locally Bounded Errors
- Aggregating inconsistent information
- Approximation algorithm for the correlation clustering problem with non-uniform hard constrained cluster sizes