A polynomial time iterative algorithm for matching Gaussian matrices with non-vanishing correlation
December 28, 2022 Β· Declared Dead Β· π Foundations of Computational Mathematics
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Jian Ding, Zhangsong Li
arXiv ID
2212.13677
Category
cs.DS: Data Structures & Algorithms
Cross-listed
math.PR,
math.ST,
stat.ML
Citations
13
Venue
Foundations of Computational Mathematics
Last Checked
3 months ago
Abstract
Motivated by the problem of matching vertices in two correlated ErdΕs-RΓ©nyi 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.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Data Structures & Algorithms
π
π
The Cartographer
R.I.P.
π»
Ghosted
Route Planning in Transportation Networks
R.I.P.
π»
Ghosted
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
R.I.P.
π»
Ghosted
Hierarchical Clustering: Objective Functions and Algorithms
R.I.P.
π»
Ghosted
Graph Isomorphism in Quasipolynomial Time
π
π
The Cartographer
Simulation optimization: A review of algorithms and applications
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted