Randomized block-coordinate adaptive algorithms for nonconvex optimization problems-Reference-Cited by-同舟云学术

Randomized block-coordinate adaptive algorithms for nonconvex optimization problems

Published:2023-05 Issue: Volume:121 Page:105968
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Zhou Yangfan^ORCID,Huang Kaizhu^ORCID,Li Jiang,Cheng Cheng,Wang Xuguang,Hussian Amir,Liu Xin^ORCID

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference37 articles.

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3. Balles, L., Hennig, P., 2018. Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients. In: Proceedings of the 35th International Conference on Machine Learning. pp. 413–422.

4. Chen, X., Liu, S., Sun, R., Hong, M., 2019. On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization. In: International Conference on Learning Representations. https://openreview.net/forum?id=H1x-x309tm.

5. Diakonikolas, J., Orecchia, L., 2018. Alternating Randomized Block Coordinate Descent. In: Proceedings of the 35th International Conference on Machine Learning. pp. 1232–1240.

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