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Gaussian belief propagation (BP) has been widely used for distributed inference in large-scale networks such as the smart grid, sensor networks, and social networks, where local measurements/observations are scattered over a wide geographical area.
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——, “Network-wide distributed carrier frequency offsets estimation and compensation via belief propagation,” IEEE Trans. Signal Process. , vol. 61, no. 23, pp. 5868–5877, 2013
2013
Cited alongside, same era.
——, “Fully distributed clock skew and offset estimation in wireless sensor networks,” in Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on , 2013, pp. 4499–4503
2013
Cited alongside, same era.
J. Du and Y.-C. Wu, “Distributed cfos estimation and compensation in multi-cell cooperative networks,” in International Conference on Information and Communication Technology Convergence , 2013
2013
Cited alongside, same era.
J. Du, S. Ma, Y.-C. Wu, S. Kar, and J. M. F. Moura, “Convergence analysis of distributed inference with vector-valued Gaussian belief propagation,” submitted for publication [Preprint Available]: https://users.ece.cmu.edu/~soummyak/GBP_convergence
Cited in the paper.
J. Du, S. Ma, Y.-C. Wu, and H. V. Poor, “Distributed bayesian hybrid power state estimation with PMU synchronization errors,” in Global Communications Conference, 2014 IEEE , 2014, pp. 3174–3179
2014
Later among the works it cites.
J. Du, S. Ma, Y.-C. Wu, S. Kar, and J. M. F. Moura, “Convergence analysis of the information matrix in Gaussian belief propagation,” in Proc. IEEE Acoustics, Speech and Signal Processing Conf. (ICASSP 2017) , 2017
2017
Closest in time.
J. Du, , S. Kar, and J. M. F. Moura, “Distributed convergence verification for gaussian belief propagation,” to appear in 2017 Asilomar Conference on Signals, Systems, and Computers
2017
Closest in time.