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2,294
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1996
"... We present a novel statistical and variational approach to image segmentation based on a new algorithm named region competition. This algorithm is derived by minimizing a generalized Bayes/MDL criterion using the variational principle. The algorithm is guaranteed to converge to a local minimum and c ..."
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Cited by 774 (20 self)
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We present a novel statistical and variational approach to image segmentation based on a new algorithm named region competition. This algorithm is derived by minimizing a generalized Bayes/MDL criterion using the variational principle. The algorithm is guaranteed to converge to a local minimum
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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FletcherGoldfarbShanno memoryless quasiNewton algorithm (BFGS) [1]. SCG yields a speedup of at least an order of magnitude relative to BP. The speedup depends on the convergence criterion, i.e., the bigger demand for reduction in error the bigger the speedup. SCG is fully automated including no user dependent parameters
Unsupervised learning of finite mixture models
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2002
"... This paper proposes an unsupervised algorithm for learning a finite mixture model from multivariate data. The adjective ªunsupervisedº is justified by two properties of the algorithm: 1) it is capable of selecting the number of components and 2) unlike the standard expectationmaximization (EM) alg ..."
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Cited by 418 (22 self)
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) algorithm, it does not require careful initialization. The proposed method also avoids another drawback of EM for mixture fitting: the possibility of convergence toward a singular estimate at the boundary of the parameter space. The novelty of our approach is that we do not use a model selection criterion
An EM Algorithm for WaveletBased Image Restoration
, 2002
"... This paper introduces an expectationmaximization (EM) algorithm for image restoration (deconvolution) based on a penalized likelihood formulated in the wavelet domain. Regularization is achieved by promoting a reconstruction with lowcomplexity, expressed in terms of the wavelet coecients, taking a ..."
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Cited by 352 (22 self)
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process requiring O(N log N) operations per iteration. Thus, it is the rst image restoration algorithm that optimizes a waveletbased penalized likelihood criterion and has computational complexity comparable to that of standard wavelet denoising or frequency domain deconvolution methods. The convergence
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
Optimal Monetary Policy in a Currency Area
, 2001
"... This paper investigates how monetary policy should be conducted in a tworegion, general equilibrium model with monopolistic competition and price stickiness. This framework delivers a simple welfare criterion based on the utility of the consumers that has the usual tradeoff between stabilizing infl ..."
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Cited by 248 (3 self)
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This paper investigates how monetary policy should be conducted in a tworegion, general equilibrium model with monopolistic competition and price stickiness. This framework delivers a simple welfare criterion based on the utility of the consumers that has the usual tradeoff between stabilizing
The PATH Solver: A NonMonotone Stabilization Scheme for Mixed Complementarity Problems
 OPTIMIZATION METHODS AND SOFTWARE
, 1995
"... The Path solver is an implementation of a stabilized Newton method for the solution of the Mixed Complementarity Problem. The stabilization scheme employs a pathgeneration procedure which is used to construct a piecewiselinear path from the current point to the Newton point; a step length acceptan ..."
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Cited by 213 (40 self)
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acceptance criterion and a nonmonotone pathsearch are then used to choose the next iterate. The algorithm is shown to be globally convergent under assumptions which generalize those required to obtain similar results in the smooth case. Several implementation issues are discussed, and extensive
The sample average approximation method for stochastic discrete optimization
 SIAM Journal on Optimization
, 2001
"... Abstract. In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and consequently the expected value function is approximated by the corresponding sample average function. The ob ..."
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Cited by 213 (21 self)
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. The obtained sample average optimization problem is solved, and the procedure is repeated several times until a stopping criterion is satisfied. We discuss convergence rates and stopping rules of this procedure and present a numerical example of the stochastic knapsack problem. Key words. Stochastic
A theory of the storage and retrieval of item and associative information
 Psychological Review
, 1982
"... A theory for the storage and retrieval of item and associative information is presented. In the theory, items or events are represented as random vectors. Convolution is used as the storage operation, and correlation is used as the retrieval operation. A distributedmemory system is assumed; all inf ..."
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Cited by 215 (5 self)
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information is stored in a common memory vector. The theory applies to both recognition and recall and covers both accuracy and latency. Noise in the decision stage necessitates a twocriterion decision system, and over time the criteria converge until a decision is reached. Performance is predicted from
Jacobi Angles For Simultaneous Diagonalization.
 SIAM J. Mat. Anal. Appl
, 1996
"... . Simultaneous diagonalization of several matrices can be implemented by a Jacobilike technique. This note gives the required Jacobi angles in close form. Key words. Simultaneous diagonalization, Jacobi iterations, eigenvalues, eigenvectors, structured eigenvalue problem. AMS subject classificati ..."
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Cited by 192 (3 self)
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classifications. 65F15, 6504. Introduction. Simultaneous diagonalization of several commuting matrices has been recently considered in [1], mainly motivated by stability and convergence concerns. Exact or approximate simultaneous diagonalization was also independently introduced as a solution to a statistical
Results 1  10
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