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Messagepassing Algorithms for
"... Abstract Messagepassing algorithms can solve a wide variety of optimization, inference, and constraint satisfaction problems. The algorithms operate on factor graphs that visually represent the problems. After describing some of their applications, I survey the family of belief propagation (BP) al ..."
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Abstract Messagepassing algorithms can solve a wide variety of optimization, inference, and constraint satisfaction problems. The algorithms operate on factor graphs that visually represent the problems. After describing some of their applications, I survey the family of belief propagation (BP
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
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
Expander graph arguments for message passing algorithms
 IEEE Trans. on Inform. Theory
, 2001
"... We show how expander based arguments may be used to prove that message passing algorithms can correct a linear number of erroneous messages. The implication of this result is that when the block length is sufficiently large, once a message passing algorithm has corrected a sufficiently large fractio ..."
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We show how expander based arguments may be used to prove that message passing algorithms can correct a linear number of erroneous messages. The implication of this result is that when the block length is sufficiently large, once a message passing algorithm has corrected a sufficiently large
Results 1  10
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