Add to ORKGIn this paper, the paradigm of linear detection is being reformulated as a Gaussian belief propagation (GaBP) scheme, without resorting to direct matrix inversion. The derived iterative framework allows for a distributive message-passing implementation of this important class of sub-optimal tractable estimators. The properties of GaBP-based linear detection are addressed, while its faster convergence, in comparison with conventional iterative solution methods, is demonstrated experimentally.
Abstract—We apply Guo and Wang’s relaxed belief propaga-tion (BP) method to the estimation of a rand...
Gaussian belief propagation (BP) is known to be an efficient message-passing algorithm for calculati...
Expectation propagation (EP) has been used for Gaussian approximation of discrete-valued symbols to ...
Abstract — The canonical problem of solving a system of linear equations arises in numerous contexts...
Abstract — In this work, we present a novel construction for solving the linear multiuser detection ...
Various ideas have been borrowed from 1D inter symbol interference (ISI) detectors towards approxima...
We introduce a message passing belief propagation (BP) algorithm for factor graph over linear models...
Abstract—We consider the estimation of an i.i.d. random vector observed through a linear transform f...
We investigate the construction of an iterative algorithm for signal detection based on Pearl's Beli...
Gaussian belief propagation (GaBP) is an iterative algorithm for computing the mean (and variances) ...
Belief propagation (BP) on cyclic graphs is an efficient algorithm for computing approximate margina...
We present an implementation-oriented algorithm for the recently developed Gaussian Belief Propagati...
Despite of its wide success in many distributed statistical learning applications, the well-known Ga...
In this paper, we propose a reduced complexity Generalized Belief Propagation (GBP) that propagates ...
How can we tell when accounts are fake or real in a social network? And how can we tell which accoun...
Abstract—We apply Guo and Wang’s relaxed belief propaga-tion (BP) method to the estimation of a rand...
Gaussian belief propagation (BP) is known to be an efficient message-passing algorithm for calculati...
Expectation propagation (EP) has been used for Gaussian approximation of discrete-valued symbols to ...
Abstract — The canonical problem of solving a system of linear equations arises in numerous contexts...
Abstract — In this work, we present a novel construction for solving the linear multiuser detection ...
Various ideas have been borrowed from 1D inter symbol interference (ISI) detectors towards approxima...
We introduce a message passing belief propagation (BP) algorithm for factor graph over linear models...
Abstract—We consider the estimation of an i.i.d. random vector observed through a linear transform f...
We investigate the construction of an iterative algorithm for signal detection based on Pearl's Beli...
Gaussian belief propagation (GaBP) is an iterative algorithm for computing the mean (and variances) ...
Belief propagation (BP) on cyclic graphs is an efficient algorithm for computing approximate margina...
We present an implementation-oriented algorithm for the recently developed Gaussian Belief Propagati...
Despite of its wide success in many distributed statistical learning applications, the well-known Ga...
In this paper, we propose a reduced complexity Generalized Belief Propagation (GBP) that propagates ...
How can we tell when accounts are fake or real in a social network? And how can we tell which accoun...
Abstract—We apply Guo and Wang’s relaxed belief propaga-tion (BP) method to the estimation of a rand...
Gaussian belief propagation (BP) is known to be an efficient message-passing algorithm for calculati...
Expectation propagation (EP) has been used for Gaussian approximation of discrete-valued symbols to ...