Randomized Sketching Algorithms for Low-Memory Dynamic Optimization-Reference-Cited by-同舟云学术

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Randomized Sketching Algorithms for Low-Memory Dynamic Optimization

Published:2021-01 Issue:2 Volume:31 Page:1242-1275
ISSN:1052-6234
Container-title:SIAM Journal on Optimization
language:en
Short-container-title:SIAM J. Optim.

Author:

Muthukumar Ramchandran,Kouri Drew P.^ORCID,Udell Madeleine^ORCID

Funder

Defense Advanced Research Projects Agency

Office of Naval Research

Sandia National Laboratories

National Science Foundation

Simons Foundation

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Theoretical Computer Science,Software

Link

https://epubs.siam.org/doi/pdf/10.1137/19M1272561

Reference31 articles.

1. Optical tomography: forward and inverse problems

2. Optimal Multistage Algorithm for Adjoint Computation

3. Optimal principal component analysis in distributed and streaming models

4. Towards efficient backward-in-time adjoint computations using data compression techniques

Cited by 4 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. Local convergence analysis of an inexact trust-region method for nonsmooth optimization;Optimization Letters;2024-02-21

2. An inexact semismooth Newton method with application to adaptive randomized sketching for dynamic optimization;Finite Elements in Analysis and Design;2024-01

3. Adaptive Randomized Sketching for Dynamic Nonsmooth Optimization;Model Validation and Uncertainty Quantification, Volume 3;2023-06-19

4. A proximal trust-region method for nonsmooth optimization with inexact function and gradient evaluations;Mathematical Programming;2022-12-26

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