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Message Passing Algorithms
, 2014
"... Message passing algorithms are some newly developed algorithms in context of telecommunication engineering in which one can perform the algorithm over different parallel machines. The first use of these algorithms were in the context of graphical models for computing the marginal pdf of some random ..."
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Message passing algorithms are some newly developed algorithms in context of telecommunication engineering in which one can perform the algorithm over different parallel machines. The first use of these algorithms were in the context of graphical models for computing the marginal pdf of some random
Entropy Message Passing Algorithm
, 2009
"... Message passing over factor graph can be considered as generalization of many well known algorithms for efficient marginalization of multivariate function. A specific instance of the algorithm is obtained by choosing an appropriate commutative semiring for the range of the function to be marginalize ..."
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Message passing over factor graph can be considered as generalization of many well known algorithms for efficient marginalization of multivariate function. A specific instance of the algorithm is obtained by choosing an appropriate commutative semiring for the range of the function
Approximate message passing algorithms for . . .
, 2014
"... Recent developments in compressive sensing (CS) combined with increasing demands for effective highdimensional inference techniques across a variety of disciplines have motivated extensive research into algorithms exploiting various notions of parsimony, including sparsity and lowrank constraints. ..."
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. In this dissertation, we extend the generalized approximate message passing (GAMP) approach, originally proposed for highdimensional generalizedlinear regression in the context of CS, to handle several classes of bilinear inference problems. First, we consider a general form of noisy CS where there is uncertainty
MessagePassing Algorithms for Quadratic Minimization
"... Gaussian belief propagation (GaBP) is an iterative algorithm for computing the mean (and variances) of a multivariate Gaussian distribution, or equivalently, the minimum of a multivariate positive definite quadratic function. Sufficient conditions, such as walksummability, that guarantee the conver ..."
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Gaussian belief propagation (GaBP) is an iterative algorithm for computing the mean (and variances) of a multivariate Gaussian distribution, or equivalently, the minimum of a multivariate positive definite quadratic function. Sufficient conditions, such as walksummability, that guarantee
SCALABLE COLLECTIVE MESSAGEPASSING ALGORITHMS
, 2011
"... Governments, universities, and companies expend vast resources building the top supercomputers. The processors and interconnect networks become faster, while the number of nodes grows exponentially. Problems of scale emerge, not least of which is collective performance. This thesis identifies and pr ..."
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the largest messages are exchanged, damaging performance. Known algorithms for torus networks use only one network port, regardless of how many are available.
Transfer Learning For Message Passing Algorithm
"... Abstract — A new learning scenario, Transfer Learning (TL) has improves learning performance when the data can be in different feature spaces and where no correspondence between data instances in these spaces is provided. Transfer learning has been used to present image clustering as an example to i ..."
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to illustrate how unsupervised learning can be improved by transferring knowledge from auxiliary data. This paper proposes a new and far more efficient method of Transfer Learning for Message Passing Algorithm. Based on this they cluster a small collection of images using readily available annotated image data
Continuouslyadaptive discretization for messagepassing algorithms
"... ContinuouslyAdaptive Discretization for MessagePassing (CADMP) is a new messagepassing algorithm for approximate inference. Most messagepassing algorithms approximate continuous probability distributions using either: a family of continuous distributions such as the exponential family; a partic ..."
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ContinuouslyAdaptive Discretization for MessagePassing (CADMP) is a new messagepassing algorithm for approximate inference. Most messagepassing algorithms approximate continuous probability distributions using either: a family of continuous distributions such as the exponential family; a
A Simple MessagePassing Algorithm for Compressed Sensing
"... Abstract—We consider the recovery of a nonnegative vector x from measurements y = Ax, where A ∈ {0, 1}m×n. We establish that when A corresponds to the adjacency matrix of a bipartite graph with sufficient expansion, a simple messagepassing algorithm produces an estimate x ̂ of x satisfying ‖x−x̂‖1 ..."
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Abstract—We consider the recovery of a nonnegative vector x from measurements y = Ax, where A ∈ {0, 1}m×n. We establish that when A corresponds to the adjacency matrix of a bipartite graph with sufficient expansion, a simple messagepassing algorithm produces an estimate x ̂ of x satisfying ‖x
MessagePassing Algorithms for the Verification of Distributed Protocols
"... Abstract. Messagepassing algorithms (MPAs) are an algorithmic paradigm for the following generic problem: given a system consisting of several interacting components, compute a new version of each component representing its behaviour inside the system. MPAs avoid computing the full state space by ..."
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Abstract. Messagepassing algorithms (MPAs) are an algorithmic paradigm for the following generic problem: given a system consisting of several interacting components, compute a new version of each component representing its behaviour inside the system. MPAs avoid computing the full state space
Results 1  10
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