Corpus ID: 207870251

# Iterative Algorithm for Discrete Structure Recovery

@article{Gao2019IterativeAF,
title={Iterative Algorithm for Discrete Structure Recovery},
author={C. Gao and A. Zhang},
journal={arXiv: Statistics Theory},
year={2019}
}
• Published 2019
• Mathematics
• arXiv: Statistics Theory
We propose a general modeling and algorithmic framework for discrete structure recovery that can be applied to a wide range of problems. Under this framework, we are able to study the recovery of clustering labels, ranks of players, and signs of regression coefficients from a unified perspective. A simple iterative algorithm is proposed for discrete structure recovery, which generalizes methods including Lloyd's algorithm and the iterative feature matching algorithm. A linear convergence result… Expand
6 Citations

#### References

SHOWING 1-10 OF 84 REFERENCES
Optimal Variable Selection and Adaptive Noisy Compressed Sensing
• Computer Science, Mathematics
• IEEE Transactions on Information Theory
• 2020
• 12
• Highly Influential
• PDF
Achieving Exact Cluster Recovery Threshold via Semidefinite Programming: Extensions
• Mathematics, Computer Science
• IEEE Transactions on Information Theory
• 2016
• 107
Partial recovery bounds for clustering with the relaxed K-means
• Mathematics, Computer Science
• ArXiv
• 2018
• 31
• PDF
Achieving Optimal Misclassification Proportion in Stochastic Block Models
• Computer Science, Mathematics
• J. Mach. Learn. Res.
• 2017
• 150
• PDF
Hard Thresholding Pursuit: An Algorithm for Compressive Sensing
• S. Foucart
• Mathematics, Computer Science
• SIAM J. Numer. Anal.
• 2011
• 354
• PDF
Exponential Error Rates of SDP for Block Models: Beyond Grothendieck’s Inequality
• Computer Science, Mathematics
• IEEE Transactions on Information Theory
• 2019
• 23
• PDF