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Matrix Concentration for Products

Huang, De and Niles-Weed, Jonathan and Tropp, Joel A. and Ward, Rachel (2021) Matrix Concentration for Products. Foundations of Computational Mathematics . ISSN 1615-3375. doi:10.1007/s10208-021-09533-9. (In Press)

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This paper develops nonasymptotic growth and concentration bounds for a product of independent random matrices. These results sharpen and generalize recent work of Henriksen–Ward, and they are similar in spirit to the results of Ahlswede–Winter and of Tropp for a sum of independent random matrices. The argument relies on the uniform smoothness properties of the Schatten trace classes.

Item Type:Article
Related URLs:
URLURL TypeDescription ReadCube access Paper
Huang, De0000-0003-4023-9895
Tropp, Joel A.0000-0003-1024-1791
Additional Information:© SFoCM 2021. Received 04 April 2020; Revised 04 March 2021; Accepted 17 June 2021; Published 13 August 2021. The authors gratefully acknowledge the funding for this work. DH was supported under NSF Grant DMS-1613861. JNW and RW were supported in part by the Institute for Advanced Study, where some of this research was conducted. JAT was supported under ONR Awards N00014-17-1-2146 and N00014-18-1-2363. RW also received support from AFOSR MURI Award N00014-17-S-F006. Communicated by Alan Edelman.
Funding AgencyGrant Number
Institute for Advanced StudyUNSPECIFIED
Office of Naval Research (ONR)N00014-17-1-2146
Office of Naval Research (ONR)N00014-18-1-2363
Air Force Office of Scientific Research (AFOSR)N00014-17-S-F006
Subject Keywords:Random matrices; Large deviation
Classification Code:Mathematics Subject Classification: 60B20; 60F10; 47B10
Record Number:CaltechAUTHORS:20201218-154434116
Persistent URL:
Official Citation:Huang, D., Niles-Weed, J., Tropp, J.A. et al. Matrix Concentration for Products. Found Comput Math (2021).
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107219
Deposited By: George Porter
Deposited On:21 Dec 2020 15:39
Last Modified:16 Nov 2021 19:00

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