Open AccessProceedings Article
A new node Centroid algorithm for bandwidth minimization
Andrew Lim,Brian Rodrigues,Fei Xiao +2 more
- 09 Aug 2003
- pp 1544-1545
TL;DR: A Node Centroid method with Hill-Climbing is proposed to solve the well-known matrix bandwidth minimization problem, which is to permute rows and columns of the matrix to minimize its bandwidth.
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Abstract: We propose a Node Centroid method with Hill-Climbing to solve the well-known matrix bandwidth minimization problem, which is to permute rows and columns of the matrix to minimize its bandwidth. Many heuristics have been developed for this NP-complete problem including the Cuthill-McKee (CM) and the Gibbs, Poole and Stockmeyer (GPS) algorithms. Recently, heuristics such as Simulated Annealing, Tabu Search and GRASP have been used, where Tabu Search and the GRASP with Path Relinking have achieved significantly better solution quality than the CM and GPS algorithms. Experimentation shows that the Node Centroid method achieves the best solution quality when compared with these while being much faster than the newly-developed algorithms.
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Citations
An evaluation of low-cost heuristics for matrix bandwidth and profile reductions
TL;DR: In this article, the authors found 132 heuristics that have been applied to these problems in reviews of the literature and selected 14 of them for which no other simulation or comparison revealed that the heuristic could be superseded by any other algorithm in the analyzed articles with respect to bandwidth or profile reduction.
37
An evaluation of reordering algorithms to reduce the computational cost of the incomplete Cholesky-conjugate gradient method
TL;DR: Numerical results confirm the effectiveness of this modified reordering algorithm for linear systems derived from specific application areas and the most promising heuristics for several application areas are identified when reducing the computational cost of the incomplete Cholesky-conjugate gradient method.
33
Metaheuristic-based Heuristics for Symmetric-matrix Bandwidth Reduction: A Systematic Review☆
Guilherme Oliveira Chagas,Sanderson L. Gonzaga de Oliveira +1 more
- 01 Jan 2015
TL;DR: Heuristics for bandwidth reduction are revised in this study, aiming at determining which of them offers the higher bandwidth reduction with a reasonable computational cost.
26
Banded Pattern Mining For N-Dimensional Zero-One Data
Fatimah Binta Abdullahi
- 24 Oct 2016
TL;DR: This thesis investigates and evaluates a series of techniques directed at identifying banded patterns in zero-one data, starting from 2D data and then increasing the number of dimensions to be considered to 3D and then ND, and describes and discusses each of these algorithms in detail.
1
References
•Book
The Nature of Statistical Learning Theory
Vladimir Vapnik
- 01 Jan 1995
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
46K
•Proceedings Article
On Spectral Clustering: Analysis and an algorithm
Andrew Y. Ng,Michael I. Jordan,Yair Weiss +2 more
- 03 Jan 2001
TL;DR: A simple spectral clustering algorithm that can be implemented using a few lines of Matlab is presented, and tools from matrix perturbation theory are used to analyze the algorithm, and give conditions under which it can be expected to do well.
•Dissertation
Variational Algorithms for Approximate Bayesian Inference
Matthew J. Beal
- 01 Jan 2003
TL;DR: A unified variational Bayesian (VB) framework which approximates computations in models with latent variables using a lower bound on the marginal likelihood and is compared to other methods including sampling, Cheeseman-Stutz, and asymptotic approximations such as BIC.
2.1K
A metric for distributions with applications to image databases
Yossi Rubner,Carlo Tomasi,Leonidas J. Guibas +2 more
- 04 Jan 1998
TL;DR: This paper uses the Earth Mover's Distance to exhibit the structure of color-distribution and texture spaces by means of Multi-Dimensional Scaling displays, and proposes a novel approach to the problem of navigating through a collection of color images, which leads to a new paradigm for image database search.