American Psychological Association 6th edition

Wang, G., Lei, Y., Zhang, Z., & Peng, C. (2024). 2 D-THA-ADMM: communication efficient distributed ADMM algorithm framework based on two-dimensional torus hierarchical All Reduce. International Journal of Machine Learning and Cybernetics, 15(2), 207-226. https://doi.org/10.1007/s13042-023-01903-9

ISO-690 (author-date, English)

WANG, Guozheng, LEI, Yongmei, ZHANG, Zeyu and PENG, Cunlu, 2024. 2 D-THA-ADMM: communication efficient distributed ADMM algorithm framework based on two-dimensional torus hierarchical All Reduce. International Journal of Machine Learning and Cybernetics. 1 February 2024. Vol. 15, no. 2, p. 207-226. DOI 10.1007/s13042-023-01903-9.

Modern Language Association 9th edition

Wang, G., Y. Lei, Z. Zhang, and C. Peng. “2 D-THA-ADMM: Communication Efficient Distributed ADMM Algorithm Framework Based on Two-Dimensional Torus Hierarchical All Reduce”. International Journal of Machine Learning and Cybernetics, vol. 15, no. 2, Feb. 2024, pp. 207-26, https://doi.org/10.1007/s13042-023-01903-9.

Mohr Siebeck - Recht (Deutsch - Österreich)

Wang, Guozheng/Lei, Yongmei/Zhang, Zeyu/Peng, Cunlu: 2 D-THA-ADMM: communication efficient distributed ADMM algorithm framework based on two-dimensional torus hierarchical All Reduce, International Journal of Machine Learning and Cybernetics 2024, 207-226.

Emerald - Harvard

Wang, G., Lei, Y., Zhang, Z. and Peng, C. (2024), “2 D-THA-ADMM: communication efficient distributed ADMM algorithm framework based on two-dimensional torus hierarchical All Reduce”, International Journal of Machine Learning and Cybernetics, Vol. 15 No. 2, pp. 207-226.

Warning: These citations may not always be 100% accurate.