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Results 11 - 20
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32,915
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2001
"... After [10, 15, 12, 2, 4] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in low-level vision. The combinatorial optimization literature provides many min-cut/max-flow algorithms with different polynomial time compl ..."
Abstract
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Cited by 1315 (53 self)
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After [10, 15, 12, 2, 4] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in low-level vision. The combinatorial optimization literature provides many min-cut/max-flow algorithms with different polynomial time
Interior-point Methods
, 2000
"... The modern era of interior-point methods dates to 1984, when Karmarkar proposed his algorithm for linear programming. In the years since then, algorithms and software for linear programming have become quite sophisticated, while extensions to more general classes of problems, such as convex quadrati ..."
Abstract
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Cited by 612 (15 self)
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quadratic programming, semidefinite programming, and nonconvex and nonlinear problems, have reached varying levels of maturity. We review some of the key developments in the area, including comments on both the complexity theory and practical algorithms for linear programming, semidefinite programming
A comparative analysis of selection schemes used in genetic algorithms
- Foundations of Genetic Algorithms
, 1991
"... This paper considers a number of selection schemes commonly used in modern genetic algorithms. Specifically, proportionate reproduction, ranking selection, tournament selection, and Genitor (or «steady state") selection are compared on the basis of solutions to deterministic difference or d ..."
Abstract
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Cited by 531 (31 self)
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This paper considers a number of selection schemes commonly used in modern genetic algorithms. Specifically, proportionate reproduction, ranking selection, tournament selection, and Genitor (or «steady state") selection are compared on the basis of solutions to deterministic difference
Fast and robust fixed-point algorithms for independent component analysis
- IEEE TRANS. NEURAL NETW
, 1999
"... Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible. In this paper, we use a combination of two different approaches for linear ICA: Comon’s informat ..."
Abstract
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Cited by 884 (34 self)
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variance. Finally, we introduce simple fixed-point algorithms for practical optimization of the contrast functions. These algorithms optimize the contrast functions very fast and reliably.
The ensemble Kalman Filter: Theoretical formulation and practical implementation.
- Ocean Dynamics,
, 2003
"... Abstract The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group and numerous publications have discussed applications and theoretical aspects of it. This paper rev ..."
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Cited by 496 (5 self)
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reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal
An empirical comparison of voting classification algorithms: Bagging, boosting, and variants.
- Machine Learning,
, 1999
"... Abstract. Methods for voting classification algorithms, such as Bagging and AdaBoost, have been shown to be very successful in improving the accuracy of certain classifiers for artificial and real-world datasets. We review these algorithms and describe a large empirical study comparing several vari ..."
Abstract
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Cited by 707 (2 self)
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Abstract. Methods for voting classification algorithms, such as Bagging and AdaBoost, have been shown to be very successful in improving the accuracy of certain classifiers for artificial and real-world datasets. We review these algorithms and describe a large empirical study comparing several
Making Large-Scale Support Vector Machine Learning Practical
, 1998
"... Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large lea ..."
Abstract
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Cited by 628 (1 self)
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algorithmic and computational results developed for SVM light V2.0, which make large-scale SVM training more practical. The results give guidelines for the application of SVMs to large domains.
Wallflower: Principles and Practice of Background Maintenance
, 1999
"... Background maintenance is a frequent element of video surveillance systems. We develop Wallflower, a three-component system for background maintenance: the pixel-level component performs Wiener filtering to make probabilistic predictions of the expected background; the region-level component fills i ..."
Abstract
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Cited by 477 (1 self)
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in homogeneous regions of foreground objects; and the frame-level component detects sudden, global changes in the image and swaps in better approximations of the background. We compare our system with 8 other background subtraction algorithms. Wallflower is shown to outperform previous algorithms by handling a
Complexity Results and Practical Algorithms for Logics in Knowledge Representation
, 2001
"... Description Logics (DLs) are used in knowledge-based systems to represent and reason about terminological knowledge of the application domain in a semantically well-defined manner. In this thesis, we establish a number of novel complexity results and give practical algorithms for expressive DLs that ..."
Abstract
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Cited by 189 (0 self)
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Description Logics (DLs) are used in knowledge-based systems to represent and reason about terminological knowledge of the application domain in a semantically well-defined manner. In this thesis, we establish a number of novel complexity results and give practical algorithms for expressive DLs
A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots
- Machine Learning
, 1998
"... . This paper addresses the problem of building large-scale geometric maps of indoor environments with mobile robots. It poses the map building problem as a constrained, probabilistic maximum-likelihood estimation problem. It then devises a practical algorithm for generating the most likely map from ..."
Abstract
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Cited by 483 (43 self)
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. This paper addresses the problem of building large-scale geometric maps of indoor environments with mobile robots. It poses the map building problem as a constrained, probabilistic maximum-likelihood estimation problem. It then devises a practical algorithm for generating the most likely map from
Results 11 - 20
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32,915
