A Polynomial Time Iterative Algorithm for Matching Gaussian Matrices with Non-vanishing Correlation
Copyright policy )A Polynomial Time Iterative Algorithm for Matching Gaussian Matrices with Non-vanishing Correlation
Motivated by the problem of matching vertices in two correlated Erdős-Rényi graphs, we study the problem of matching two correlated Gaussian Wigner matrices. We propose an iterative matching algorithm, which succeeds in polynomial time as long as the correlation between the two Gaussian matrices does not vanish. Our result is the first polynomial time algorithm that solves a graph matching type of problem when the correlation is an arbitrarily small constant.
51 pages
- Peking University China (People's Republic of)
- Peking University China (People's Republic of)
- Hebei University China (People's Republic of)
- Peking University China (People's Republic of)
- Peking University
computation transition, FOS: Computer and information sciences, random graph matching, Data Structures and Algorithms, Graphs and linear algebra (matrices, eigenvalues, etc.), iterative algorithms, Probability (math.PR), Random graphs (graph-theoretic aspects), Machine Learning (stat.ML), Statistics Theory (math.ST), Programming involving graphs or networks, Machine Learning, Edge subsets with special properties (factorization, matching, partitioning, covering and packing, etc.), Graph algorithms (graph-theoretic aspects), correlated Wigner matrices, Statistics Theory, FOS: Mathematics, Data Structures and Algorithms (cs.DS), Probability
computation transition, FOS: Computer and information sciences, random graph matching, Data Structures and Algorithms, Graphs and linear algebra (matrices, eigenvalues, etc.), iterative algorithms, Probability (math.PR), Random graphs (graph-theoretic aspects), Machine Learning (stat.ML), Statistics Theory (math.ST), Programming involving graphs or networks, Machine Learning, Edge subsets with special properties (factorization, matching, partitioning, covering and packing, etc.), Graph algorithms (graph-theoretic aspects), correlated Wigner matrices, Statistics Theory, FOS: Mathematics, Data Structures and Algorithms (cs.DS), Probability
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