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Loopy belief propagation for approximate inference: An empirical study. In:
 Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" the use of Pearl's polytree algorithm in a Bayesian network with loops can perform well in the context of errorcorrecting codes. The most dramatic instance of this is the near Shannonlimit performanc ..."
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Cited by 676 (15 self)
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with loops (undirected cycles). The algorithm is an exact inference algorithm for singly connected networks the beliefs converge to the cor rect marginals in a number of iterations equal to the diameter of the graph.1 However, as Pearl noted, the same algorithm will not give the correct beliefs for mul
Iterative Methods For Total Variation Denoising
 SIAM J. SCI. COMPUT
"... Total Variation (TV) methods are very effective for recovering "blocky", possibly discontinuous, images from noisy data. A fixed point algorithm for minimizing a TVpenalized least squares functional is presented and compared with existing minimization schemes. A variant of the cellcenter ..."
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Cited by 341 (7 self)
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centered finite difference multigrid method of Ewing and Shen is implemented for solving the (large, sparse) linear subproblems. Numerical results are presented for one and twodimensional examples; in particular, the algorithm is applied to actual data obtained from confocal microscopy.
A scaled conjugate gradient algorithm for fast supervised learning
 NEURAL NETWORKS
, 1993
"... A supervised learning algorithm (Scaled Conjugate Gradient, SCG) with superlinear convergence rate is introduced. The algorithm is based upon a class of optimization techniques well known in numerical analysis as the Conjugate Gradient Methods. SCG uses second order information from the neural netwo ..."
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Cited by 451 (0 self)
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A supervised learning algorithm (Scaled Conjugate Gradient, SCG) with superlinear convergence rate is introduced. The algorithm is based upon a class of optimization techniques well known in numerical analysis as the Conjugate Gradient Methods. SCG uses second order information from the neural
Numerical solution of saddle point problems
 ACTA NUMERICA
, 2005
"... Large linear systems of saddle point type arise in a wide variety of applications throughout computational science and engineering. Due to their indefiniteness and often poor spectral properties, such linear systems represent a significant challenge for solver developers. In recent years there has b ..."
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Cited by 322 (25 self)
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been a surge of interest in saddle point problems, and numerous solution techniques have been proposed for solving this type of systems. The aim of this paper is to present and discuss a large selection of solution methods for linear systems in saddle point form, with an emphasis on iterative methods
QMR: a QuasiMinimal Residual Method for NonHermitian Linear Systems
, 1991
"... ... In this paper, we present a novel BCGlike approach, the quasiminimal residual (QMR) method, which overcomes the problems of BCG. An implementation of QMR based on a lookahead version of the nonsymmetric Lanczos algorithm is proposed. It is shown how BCG iterates can be recovered stably from t ..."
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Cited by 395 (26 self)
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... In this paper, we present a novel BCGlike approach, the quasiminimal residual (QMR) method, which overcomes the problems of BCG. An implementation of QMR based on a lookahead version of the nonsymmetric Lanczos algorithm is proposed. It is shown how BCG iterates can be recovered stably from
Iterative Waterfilling for Gaussian Vector Multiple Access Channels
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 2001
"... This paper characterizes the capacity region of a Gaussian multiple access channel with vector inputs and a vector output with or without intersymbol interference. The problem of finding the optimal input distribution is shown to be a convex programming problem, and an efficient numerical algorithm ..."
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Cited by 313 (12 self)
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is developed to evaluate the optimal transmit spectrum under the maximum sum data rate criterion. The numerical algorithm has an iterative waterfilling int#j pret#4968 . It converges from any starting point and it reaches with in s per output dimension per transmission from the Kuser multiple access sum
A numerical iterative method for solving systems of firstorder periodic boundary value problems,”
 Article ID 135465, 10
, 2014
"... The objective of this paper is to present a numerical iterative method for solving systems of firstorder ordinary differential equations subject to periodic boundary conditions. This iterative technique is based on the use of the reproducing kernel Hilbert space method in which every function sati ..."
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Cited by 1 (1 self)
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The objective of this paper is to present a numerical iterative method for solving systems of firstorder ordinary differential equations subject to periodic boundary conditions. This iterative technique is based on the use of the reproducing kernel Hilbert space method in which every function
Probing the Pareto frontier for basis pursuit solutions
, 2008
"... The basis pursuit problem seeks a minimum onenorm solution of an underdetermined leastsquares problem. Basis pursuit denoise (BPDN) fits the leastsquares problem only approximately, and a single parameter determines a curve that traces the optimal tradeoff between the leastsquares fit and the ..."
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Cited by 365 (5 self)
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on this curve; the algorithm is suitable for problems that are large scale and for those that are in the complex domain. At each iteration, a spectral gradientprojection method approximately minimizes a leastsquares problem with an explicit onenorm constraint. Only matrixvector operations are required
6th INTERNATIONAL MULTIDISCIPLINARY CONFERENCE THE FRACTAL TECHNIQUES APPLIED IN NUMERICAL ITERATIVE METHODS FRAME
"... Abstract: Many methods in the numeric calculus resolving nonlinear algebraic or differential equation but ignore some behavior of these problems. Same aspects can conjure to the fractal iterative techniques. In this paper work is performed a critical analysis about iterative fractal techniques which ..."
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Abstract: Many methods in the numeric calculus resolving nonlinear algebraic or differential equation but ignore some behavior of these problems. Same aspects can conjure to the fractal iterative techniques. In this paper work is performed a critical analysis about iterative fractal techniques
A NUMERICAL ITERATIVE SCHEME FOR COMPUTING FINITE ORDER RANKONE CONVEX ENVELOPES
"... Abstract. It is known that the ith order laminated microstructures can be resolved by the kth order rankone convex envelopes with k ≥ i. So the requirement of establishing an efficient numerical scheme for the computation of the finite order rankone convex envelopes arises. In this paper, we dev ..."
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Abstract. It is known that the ith order laminated microstructures can be resolved by the kth order rankone convex envelopes with k ≥ i. So the requirement of establishing an efficient numerical scheme for the computation of the finite order rankone convex envelopes arises. In this paper, we
Results 11  20
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9,396