Tightness of the maximum likelihood semidefinite relaxation for angular synchronization
نویسندگان
چکیده
منابع مشابه
Open Problem: Tightness of maximum likelihood semidefinite relaxations
We have observed an interesting, yet unexplained, phenomenon: Semidefinite programming (SDP) based relaxations of maximum likelihood estimators (MLE) tend to be tight in recovery problems with noisy data, even when MLE cannot exactly recover the ground truth. Several results establish tightness of SDP based relaxations in the regime where exact recovery from MLE is possible. However, to the bes...
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The angular synchronization problem is to obtain an accurate estimation (up to a constant additive phase) for a set of unknown angles θ(1), …, θ(n) from m noisy measurements of their offsets θ(i) - θ(j) mod 2π. Of particular interest is angle recovery in the presence of many outlier measurements that are uniformly distributed in [0, 2π) and carry no information on the true offsets. We introduce...
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Many signal processing applications reduce to solving integer least square problems, e.g., Maximum Likelihood (ML) detection, which is NP-hard. Recently semidefinite programming (SDP) approach has been shown to be promising approach to combinatorial problems. SDP methods have been applied to the communications problem, e.g., [1], [2], [3]. But so far no theoretical analysis of the algorithm is ...
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ژورنال
عنوان ژورنال: Mathematical Programming
سال: 2016
ISSN: 0025-5610,1436-4646
DOI: 10.1007/s10107-016-1059-6