Optimal Dynamic Regret for Online Convex Optimization with Squared l<sub>2</sub> Norm Switching Cost-Reference-Cited by-同舟云学术

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Optimal Dynamic Regret for Online Convex Optimization with Squared l₂ Norm Switching Cost

Published:2022-06-08 Issue: Volume: Page:
ISSN:
Container-title:2022 American Control Conference (ACC)
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Author:

Liu Qingsong¹,Zhang Yaoyu¹

Affiliation:

1. Tsinghua University,Institute for Interdisciplinary Information Sciences,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9866948/9867142/09867328.pdf?arnumber=9867328

Reference17 articles.

1. Online optimization with predictions and switching costs: Fast algorithms and the fundamental limit;li;IEEE Transactions on Automatic Control,2020

2. Improved dynamic regret for non-degenerate functions;zhang;Advances in neural information processing systems,2017

Cited by 2 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. Learning To Regularized Resource Allocation with Budget Constraints;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

2. The optimal dynamic regret for smoothed online convex optimization with squared l2 norm switching costs;Journal of the Franklin Institute;2023-04

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