Distributed Sketching for Randomized Optimization: Exact Characterization, Concentration, and Lower Bounds-Reference-Cited by-同舟云学术

Distributed Sketching for Randomized Optimization: Exact Characterization, Concentration, and Lower Bounds

Published:2023-06 Issue:6 Volume:69 Page:3850-3879
ISSN:0018-9448
Container-title:IEEE Transactions on Information Theory
language:
Short-container-title:IEEE Trans. Inform. Theory

Author:

Bartan Burak¹^ORCID,Pilanci Mert¹^ORCID

Affiliation:

1. Department of Electrical Engineering, Stanford University, Stanford, CA, USA

Funder

National Science Foundation

NSF CAREER Award

U.S. Army Research Office Early Career Award

Stanford Precourt Institute

ACCESS—Artificial Intelligence (AI) Chip Center for Emerging Smart Systems through InnoHK, Hong Kong, SAR

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Library and Information Sciences,Computer Science Applications,Information Systems

Link

https://ieeexplore.ieee.org/ielam/18/10130037/10049613-aam.pdf

Reference44 articles.

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4. Debiasing distributed second order optimization with surrogate sketching and scaled regularization;derezinski;Proc Adv Neural Inf Process Syst,2020

5. Privacy-Utility Trade-off of Linear Regression under Random Projections and Additive Noise

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