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57,879
Ant algorithms for discrete optimization
 ARTIFICIAL LIFE
, 1999
"... This article presents an overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies’ foraging behavior, and introduces the ant colony optimization (ACO) metaheuristic. In the first part of the article the basic ..."
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Cited by 489 (42 self)
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This article presents an overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies’ foraging behavior, and introduces the ant colony optimization (ACO) metaheuristic. In the first part of the article the basic
Analysis and Simulation of a Fair Queueing Algorithm
, 1989
"... We discuss gateway queueing algorithms and their role in controlling congestion in datagram networks. A fair queueing algorithm, based on an earlier suggestion by Nagle, is proposed. Analysis and simulations are used to compare this algorithm to other congestion control schemes. We find. that fair q ..."
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Cited by 1269 (39 self)
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queueing provides several important advantages over the usual firstcomefirstserve queueing algorithm: fair allocation of bandwidth, lower delay for sources using less than their full share of bandwidth, and protection from illbehaved sources.
Inductive learning algorithms and representations for text categorization,”
 in Proceedings of the International Conference on Information and Knowledge Management,
, 1998
"... ABSTRACT Text categorization the assignment of natural language texts to one or more predefined categories based on their content is an important component in many information organization and management tasks. We compare the effectiveness of five different automatic learning algorithms for text ..."
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Cited by 652 (8 self)
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ABSTRACT Text categorization the assignment of natural language texts to one or more predefined categories based on their content is an important component in many information organization and management tasks. We compare the effectiveness of five different automatic learning algorithms for text
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
, 2000
"... In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in conver ..."
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Cited by 628 (41 self)
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, the experimental results indicate a hierarchy of the algorithms under consideration. Furthermore, the emerging effects are evidence that the suggested test functions provide sufficient complexity to compare multiobjective optimizers. Finally, elitism is shown to be an important factor for improving evolutionary
A Singular Value Thresholding Algorithm for Matrix Completion
, 2008
"... This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood as the convex relaxation of a rank minimization problem, and arises in many important applications as in the task of reco ..."
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Cited by 555 (22 self)
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This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood as the convex relaxation of a rank minimization problem, and arises in many important applications as in the task
Constructing Free Energy Approximations and Generalized Belief Propagation Algorithms
 IEEE Transactions on Information Theory
, 2005
"... Important inference problems in statistical physics, computer vision, errorcorrecting coding theory, and artificial intelligence can all be reformulated as the computation of marginal probabilities on factor graphs. The belief propagation (BP) algorithm is an efficient way to solve these problems t ..."
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Cited by 585 (13 self)
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Important inference problems in statistical physics, computer vision, errorcorrecting coding theory, and artificial intelligence can all be reformulated as the computation of marginal probabilities on factor graphs. The belief propagation (BP) algorithm is an efficient way to solve these problems
Segmentation of brain MR images through a hidden Markov random field model and the expectationmaximization algorithm
 IEEE TRANSACTIONS ON MEDICAL. IMAGING
, 2001
"... The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogrambased model, the FM has an intrinsic limi ..."
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Cited by 639 (15 self)
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methods are limited to using MRF as a general prior in an FM modelbased approach. To fit the HMRF model, an EM algorithm is used. We show that by incorporating both the HMRF model and the EM algorithm into a HMRFEM framework, an accurate and robust segmentation can be achieved. More importantly
Evolutionary Algorithms for Multiobjective Optimization
, 2002
"... Multiple, often conflicting objectives arise naturally in most realworld optimization scenarios. As evolutionary algorithms possess several characteristics due to which they are well suited to this type of problem, evolutionbased methods have been used for multiobjective optimization for more than ..."
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Cited by 450 (13 self)
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are discussed from an algorithm design perspective. The focus is on the major issues such as fitness assignment, diversity preservation, and elitism in general rather than on particular algorithms. Different techniques to implement these strongly related concepts will be discussed, and further important aspects
Practical Byzantine fault tolerance
, 1999
"... This paper describes a new replication algorithm that is able to tolerate Byzantine faults. We believe that Byzantinefaulttolerant algorithms will be increasingly important in the future because malicious attacks and software errors are increasingly common and can cause faulty nodes to exhibit arbi ..."
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Cited by 673 (15 self)
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This paper describes a new replication algorithm that is able to tolerate Byzantine faults. We believe that Byzantinefaulttolerant algorithms will be increasingly important in the future because malicious attacks and software errors are increasingly common and can cause faulty nodes to exhibit
Adaptive Constraint Satisfaction
 WORKSHOP OF THE UK PLANNING AND SCHEDULING
, 1996
"... Many different approaches have been applied to constraint satisfaction. These range from complete backtracking algorithms to sophisticated distributed configurations. However, most research effort in the field of constraint satisfaction algorithms has concentrated on the use of a single algorithm fo ..."
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Cited by 952 (43 self)
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for solving all problems. At the same time, a consensus appears to have developed to the effect that it is unlikely that any single algorithm is always the best choice for all classes of problem. In this paper we argue that an adaptive approach should play an important part in constraint satisfaction
Results 1  10
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57,879