D-ADMM: A communication-efficient distributed algorithm for separable optimization

IEEE Transactions on Signal Processing

Volumn 61, Issue 10, 2013, Pages 2718-2723

  Mota, João F C ^a,b   Xavier, João M F ^a   Aguiar, Pedro M Q ^a   Püschel, Markus ^c  

^a INSTITUTO SUPERIOR TÉCNICO   (Portugal)

^b CARNEGIE MELLON UNIVERSITY   (United States)

^c ETH ZURICH   (Switzerland)

Author keywords

Alternating direction method of multipliers; Distributed algorithms; Sensor networks.

Indexed keywords

COMPRESSED SENSING; COST FUNCTIONS; DISCRETE COSINE TRANSFORMS; OPTIMIZATION; PARALLEL ALGORITHMS; PROBLEM SOLVING; SENSOR NETWORKS; SIGNAL PROCESSING;

ACCURACY LEVEL; ALTERNATING DIRECTION METHOD OF MULTIPLIERS; AVERAGE CONSENSUS; CONSTRAINT SET; FOLLOWING PROBLEM; INTERCONNECTED NODES; OPTIMIZATION PROBLEMS; STATE-OF-THE-ART ALGORITHMS;

ALGORITHMS;

EID: 84948952391     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2013.2254478     Document Type: Article

References (28)

1. J. Mota, J. Xavier, P. Aguiar, and M. Püschel, "Distributed basis pursuit, " IEEE Trans. Signal Process., vol. 60, no. 4, pp. 1942-1956, 2012.
2. I. Akyildiz, Y. Sankarasubramaniam, and E. Cayirci, "Wireless sensor networks: A survey, " Comput. Netw., vol. 38, pp. 393-422, 2002.
3. P. Fischione, P. Park, and K. Johansson, Wireless Network Based Control, Chapter Design Principles of Wireless Sensor Network Protocols for Control Applications. New York, NY, USA: Springer, 2011.
4. S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, "Distributed optimization and statistical learning via the alternating method of multipliers, " Found. Trends Mach. Learn., vol. 3, no. 1, pp. 1-122, 2011.
5. D. Han and X. Yuan, "A note on the alternating direction method of multipliers, " J. Optim. Theory Appl., pp. 227-238, 2012.
6. J. Tsitsiklis, D. Bertsekas, and M. Athans, "Distributed asynchronous deterministic and stochastic gradient optimization algorithms, " IEEE Trans. Autom. Control, vol. AC-31, no. 9, pp. 803-812, 1986.
7. M. Rabbat and R. Nowak, "Distributed optimization in sensor networks, " in Proc. IPSN, 2004, pp. 20-27.
8. P. Palomar and Y. Eldar, Convex Optimization in Signal Processing and Communications. Cambridge, U.K.: Cambridge Univ. Press, 2010.
9. D. Bertsekas and J. Tsitsiklis, Parallel and Distributed Computation: Numerical Methods. Belmont, MA, USA: Athena Scientific, 1997.
10. D. Jakovetić, J. Xavier, and J. Moura, "Cooperative convex optimization in networked systems: Augmented lagrangian algorithms with directed gossip communication, " IEEE Trans. Signal Process., vol. 59, no. 8, pp. 3889-3902, 2011.
11. M. Rabbat, R. Nowak, and J. Bucklew, "Generalized consensus algorithms in networked systems with erasure links, " in Proc. IEEE Workshop Signal Process. Adv. Wireless Commun., 2005, pp. 1088-1092.
12. I. Schizas, A. Ribeiro, and G. Giannakis, "Consensus in ad hoc wsns with noisy links-Part I: Distributed estimation of deterministic signals, " IEEE Trans. Signal Process., vol. 56, no. 1, pp. 350-364, 2008.
13. H. Zhu, G. Giannakis, and A. Cano, "Distributed in-network channel decoding, " IEEE Trans. Signal Process., vol. 57, no. 10, pp. 3970-3983, 2009.
14. J. Bazerque and G. Giannakis, "Distributed spectrum sensing for cognitive radio networks by exploiting sparsity, " IEEE Trans. Signal Process., vol. 58, no. 3, pt. 2, pp. 1847-1862, 2010.
15. P. Forero, A. Cano, and G. Giannakis, "Consensus-based distributed support vector machines, " J. Mach. Learn. Res., vol. 11, pp. 1663-1707, 2010.
16. G. Mateos, J. Bazerque, and G. Giannakis, "Distributed sparse linear regression, " IEEE Trans. Signal Process., vol. 58, no. 10, pp. 5262-5276, 2010.
17. J. Bazerque, G. Mateos, and G. Giannakis, "Group-Lasso on splines for spectrum cartography, " IEEE Trans. Signal Process., vol. 59, no. 10, pp. 4648-4663, 2011.
18. T. Erseghe, D. Zennaro, E. Dall'Anese, and L. Vangelista, "Fast consensus by the alternating direction multipliers method, " IEEE Trans. Signal Process., vol. 59, no. 11, pp. 5523-5537, 2011.
19. J. Mota, J. Xavier, P. Aguiar, and M. Püschel, "A proof of convergence for the alternating directionmethod ofmultipliers applied to polyhedral constrained functions, " 2011 [Online]. Available: http://arxiv.org/abs/1112.2295
20. B. He, M. Tao, and X. Yuan, "Alternating direction method with Gaussian back substitution for separable convex programming, " SIAM J. Optim., vol. 22, no. 2, pp. 313-340, 2012.
21. Z. Luo, "On the linear convergence of the alternating direction method of multipliers, " 2012 [Online]. Available: arxiv.org/abs/1208.3922
22. B. Oreshkin, M. Coates, and M. Rabbat, "Optimization and analysis of distributed averaging with short node memory, " IEEE Trans. Signal Process., vol. 58, no. 5, pp. 2850-2865, 2010.
23. R. Tibshirani, "Regression shrinkage and selection via the lasso, " J. R. Statist. Soc. B, vol. 58, no. 1, pp. 267-288, 1996.
24. S. Chen, D. Donoho, and M. Saunders, "Atomic decomposition by basis pursuit, " SIAM J. Sci. Conput., vol. 20, no. 1, pp. 33-61, 1998.
25. M. Friedlander and P. Tseng, "Exact regularization of convex programs, " SIAM J. Optim., vol. 18, no. 4, pp. 1326-1350, 2007.
26. C. Bishop, Pattern Recognition and Machine Learning. NewYork, NY, USA: Springer, 2006.
27. E. Berg, M. Friedlander, G. Hennenfent, F. Herrmann, R. Saab, and O. Yilmaz, Sparco: A Testing Framework for Sparse Reconstruction Dept. Comput. Sci., Univ. of British Columbia, Vancouver, BC, Canada, Tech. Rep., 2007.
28. A. Frank and A. Asuncion, UCI Machine Learning Repository, Univ. of California, Irvine, CA, USA, 2010.