Print Email Facebook Twitter On Simplifying the Primal-Dual Method of Multipliers Title On Simplifying the Primal-Dual Method of Multipliers Author Zhang, G. (TU Delft Signal Processing Systems) Heusdens, R. (TU Delft Signal Processing Systems) Contributor Dong, Min (editor) Zheng, Thomas Fang (editor) Date 2016-05-19 Abstract Recently, the primal-dual method of multipliers (PDMM) has been proposed to solve a convex optimization problem defined over a general graph. In this paper, we consider simplifying PDMM for a subclass of the convex optimization problems. This subclass includes the consensus problem as a special form. By using algebra, we show that the update expressions of PDMM can be simplified significantly. We then evaluate PDMM for training a support vector machine (SVM). The experimental results indicate that PDMM converges considerably faster than the alternating direction method of multipliers (ADMM). Subject distributed optimizationPDMMADMMSVM To reference this document use: http://resolver.tudelft.nl/uuid:e8dcd069-3363-4cff-b6d8-e825e044956f DOI https://doi.org/10.1109/icassp.2016.7472594 Publisher IEEE, Danvers, MA ISBN 978-1-4799-9988-0 Source 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP): Proceedings Event 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016, 2016-03-20 → 2016-03-25, Shanghai International Convention Center, Shanghai, China Bibliographical note Accepted Author Manuscript Part of collection Institutional Repository Document type conference paper Rights © 2016 G. Zhang, R. Heusdens Files PDF heusdens16icassp4.pdf 221.43 KB Close viewer /islandora/object/uuid:e8dcd069-3363-4cff-b6d8-e825e044956f/datastream/OBJ/view