TY - GEN
T1 - Generalized Distributed Dual Coordinate Ascent in a Tree Network for Machine Learning
AU - Cho, Myung
AU - Lai, Lifeng
AU - Xu, Weiyu
N1 - Funding Information:
The work of W. Xu was supported in part by Simons Foundation 318608 and in part by National Science Foundation (NSF) DMS-1418737. And the work of L. Lai was supported by NSF under grants CCF-1717943, ECCS-1711468 and CNS-1824553.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - With explosion of data size and limited storage space at a single location, data are often distributed at different locations. We thus face the challenge of performing large-scale machine learning from these distributed data through communication networks. In this paper, we generalize the distributed dual coordinate ascent in a star network to a general tree structured network, and provide the convergence rate analysis of the general distributed dual coordinate ascent. In numerical experiments, we demonstrate that the performance of the distributed dual coordinate ascent in a tree network can outperform that of the distributed dual coordinate ascent in a star network when a network has a lot of communication delays between the center node and its direct child nodes.
AB - With explosion of data size and limited storage space at a single location, data are often distributed at different locations. We thus face the challenge of performing large-scale machine learning from these distributed data through communication networks. In this paper, we generalize the distributed dual coordinate ascent in a star network to a general tree structured network, and provide the convergence rate analysis of the general distributed dual coordinate ascent. In numerical experiments, we demonstrate that the performance of the distributed dual coordinate ascent in a tree network can outperform that of the distributed dual coordinate ascent in a star network when a network has a lot of communication delays between the center node and its direct child nodes.
UR - http://www.scopus.com/inward/record.url?scp=85068981658&partnerID=8YFLogxK
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U2 - 10.1109/ICASSP.2019.8682185
DO - 10.1109/ICASSP.2019.8682185
M3 - Conference contribution
AN - SCOPUS:85068981658
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 3512
EP - 3516
BT - 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Y2 - 12 May 2019 through 17 May 2019
ER -