Fundamental Limits of Weak Recovery with Applications to Phase Retrieval

Author:

Mondelli Marco,Montanari Andrea

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Analysis

Reference83 articles.

1. Arora, S., Ge, R., Ma, T., Moitra, A.: Simple, efficient, and neural algorithms for sparse coding. In: Conference on Learning Theory (COLT), pp. 113–149. Paris, France (2015)

2. Bahmani, S., Romberg, J.: Phase retrieval meets statistical learning theory: A flexible convex relaxation. In: Proc. of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 252–260. Fort Lauderdale, FL (2017)

3. Bai, Z., Yao, J.: On sample eigenvalues in a generalized spiked population model. Journal of Multivariate Analysis 106, 167–177 (2012)

4. Balan, R., Casazza, P., Edidin, D.: On signal reconstruction without phase. Applied and Computational Harmonic Analysis 20(3), 345–356 (2006)

5. Bandeira, A.S., Cahill, J., Mixon, D.G., Nelson, A.A.: Saving phase: Injectivity and stability for phase retrieval. Applied and Computational Harmonic Analysis 37(1), 106–125 (2014)

Cited by 33 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Toward Designing Optimal Sensing Matrices for Generalized Linear Inverse Problems;IEEE Transactions on Information Theory;2024-01

2. Deep Expectation-Consistent Approximation for Phase Retrieval;2023 57th Asilomar Conference on Signals, Systems, and Computers;2023-10-29

3. Bayes-Optimal Estimation in Generalized Linear Models via Spatial Coupling;2023 IEEE International Symposium on Information Theory (ISIT);2023-06-25

4. Provable sample-efficient sparse phase retrieval initialized by truncated power method;Inverse Problems;2023-06-09

5. Fundamental limits to learning closed-form mathematical models from data;Nature Communications;2023-02-24

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3