Mateda-2.0: Estimation of Distribution Algorithms in MATLAB
暂无分享,去创建一个
Concha Bielza | Pedro Larrañaga | José Antonio Lozano Alonso | Alexander Mendiburu Alberro | Roberto Santana Hermida | Siddartha Shakya | Carlos Echegoyen | Rubén Armañanzas Arnedillo | C. Bielza | P. Larrañaga | Carlos Echegoyen | Ruben Armananzas Arnedillo | A. Alberro | J. A. Alonso | S. Shakya | Roberto Santana
[1] David Heckerman,et al. Knowledge Representation and Inference in Similarity Networks and Bayesian Multinets , 1996, Artif. Intell..
[2] M. Pelikán,et al. The Bivariate Marginal Distribution Algorithm , 1999 .
[3] Pedro Larrañaga,et al. Research topics in discrete estimation of distribution algorithms based on factorizations , 2009, Memetic Comput..
[4] Michael I. Jordan,et al. Learning with Mixtures of Trees , 2001, J. Mach. Learn. Res..
[5] Fernando G. Lobo,et al. Extended Compact Genetic Algorithm in C , 1999 .
[6] William E. Hart,et al. Fast protein folding in the hydrophobic-hydrophilic model within three-eights of optimal , 1995, STOC '95.
[7] Garrison W. Greenwood,et al. On the Evolutionary Search for Solutions to the Protein Folding Problem , 2003 .
[8] Pedro Larrañaga,et al. Learning Factorizations in Estimation of Distribution Algorithms Using Affinity Propagation , 2010, Evolutionary Computation.
[9] Mihalis Yannakakis,et al. On the Complexity of Protein Folding , 1998, J. Comput. Biol..
[10] Max Henrion,et al. Propagating uncertainty in bayesian networks by probabilistic logic sampling , 1986, UAI.
[11] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[12] Kevin Murphy,et al. Bayes net toolbox for Matlab , 1999 .
[13] C. Robert Kenley,et al. Gaussian influence diagrams , 1989 .
[14] Martin Pelikan,et al. Analyzing probabilistic models in hierarchical BOA on traps and spin glasses , 2007, GECCO '07.
[15] Delbert Dueck,et al. Clustering by Passing Messages Between Data Points , 2007, Science.
[16] L. Tierney. Markov Chains for Exploring Posterior Distributions , 1994 .
[17] Alfred Inselberg,et al. Parallel Coordinates: Visual Multidimensional Geometry and Its Applications , 2003, KDIR.
[18] D. Goldberg,et al. BOA: the Bayesian optimization algorithm , 1999 .
[19] Concha Bielza,et al. A review of estimation of distribution algorithms in bioinformatics , 2008, BioData Mining.
[20] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.
[21] Qingfu Zhang,et al. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , 2007, IEEE Transactions on Evolutionary Computation.
[22] Jing-Yu Yang,et al. Optimal discriminant plane for a small number of samples and design method of classifier on the plane , 1991, Pattern Recognit..
[23] J. Laurie Snell,et al. Markov Random Fields and Their Applications , 1980 .
[24] Ernesto Costa,et al. Too Busy to Learn , 2000 .
[25] Qingfu Zhang,et al. This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 1 RM-MEDA: A Regularity Model-Based Multiobjective Estimation of , 2022 .
[26] J. A. Lozano,et al. Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation , 2001 .
[27] Philippe Leray,et al. BNT STRUCTURE LEARNING PACKAGE : Documentation and Experiments , 2004 .
[28] Rubén Armañanzas. Consensus Policies to Solve Bioinformatic Problems: Through Bayesian Network Classifiers and Estimation of Distribution Algorithms , 2012 .
[29] Siddhartha Shakya,et al. Using a Markov network model in a univariate EDA: an empirical cost-benefit analysis , 2005, GECCO '05.
[30] S. C. Johnson. Hierarchical clustering schemes , 1967, Psychometrika.
[31] David E. Goldberg,et al. Efficiency Enhancement of Estimation of Distribution Algorithms , 2006, Scalable Optimization via Probabilistic Modeling.
[32] R. Santana,et al. The mixture of trees Factorized Distribution Algorithm , 2001 .
[33] David E. Goldberg,et al. Genetic Algorithms, Clustering, and the Breaking of Symmetry , 2000, PPSN.
[34] Heinz Mühlenbein,et al. The Equation for Response to Selection and Its Use for Prediction , 1997, Evolutionary Computation.
[35] P. A. Simionescu,et al. Teeth-Number Synthesis of a Multispeed Planetary Transmission Using an Estimation of Distribution Algorithm , 2006 .
[36] Martin Pelikan. A C++ Implementation of the Bayesian Optimization Algorithm (BOA) with Decision Graphs , 2000 .
[37] Julian Besag,et al. Markov Chain Monte Carlo for Statistical Inference , 2002 .
[38] Vasant Honavar,et al. Evolutionary Synthesis of Bayesian Networks for Optimization , 2001 .
[39] Concha Bielza,et al. Machine Learning in Bioinformatics , 2008, Encyclopedia of Database Systems.
[40] Endika Bengoetxea,et al. Inexact Graph Matching Using Estimation of Distribution Algorithms , 2002 .
[41] Concha Bielza,et al. MATEDA: A suite of EDA programs in Matlab , 2009 .
[42] Qingfu Zhang,et al. Approaches to selection and their effect on fitness modelling in an Estimation of Distribution Algorithm , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).
[43] Russ B. Altman,et al. Missing value estimation methods for DNA microarrays , 2001, Bioinform..
[44] Heinz Mühlenbein,et al. The Estimation of Distributions and the Minimum Relative Entropy Principle , 2005, Evol. Comput..
[45] Raphael T. Haftka,et al. A double-distribution statistical algorithm for composite laminate optimization , 2004 .
[46] H. Mühlenbein,et al. From Recombination of Genes to the Estimation of Distributions I. Binary Parameters , 1996, PPSN.
[47] H. Akaike. A new look at the statistical model identification , 1974 .
[48] Pedro Larrañaga,et al. Adaptive Estimation of Distribution Algorithms , 2008, Adaptive and Multilevel Metaheuristics.
[49] Martin Pelikan,et al. Hierarchical Bayesian optimization algorithm: toward a new generation of evolutionary algorithms , 2010, SICE 2003 Annual Conference (IEEE Cat. No.03TH8734).
[50] N. Metropolis,et al. Equation of State Calculations by Fast Computing Machines , 1953, Resonance.
[51] Kemal Polat,et al. Computer aided medical diagnosis system based on principal component analysis and artificial immune recognition system classifier algorithm , 2008, Expert Syst. Appl..
[52] Dirk Thierens,et al. Multi-objective optimization with diversity preserving mixture-based iterated density estimation evolutionary algorithms , 2002, Int. J. Approx. Reason..
[53] S. Baluja,et al. Using Optimal Dependency-Trees for Combinatorial Optimization: Learning the Structure of the Search Space , 1997 .
[54] D. Nilsson,et al. An efficient algorithm for finding the M most probable configurationsin probabilistic expert systems , 1998, Stat. Comput..
[55] Pedro Larrañaga,et al. The Impact of Exact Probabilistic Learning Algorithms in EDAs Based on Bayesian Networks , 2008, Linkage in Evolutionary Computation.
[57] Tomi Silander,et al. A Simple Approach for Finding the Globally Optimal Bayesian Network Structure , 2006, UAI.
[58] P. Spirtes,et al. Causation, prediction, and search , 1993 .
[59] Heinz Mühlenbein,et al. Schemata, Distributions and Graphical Models in Evolutionary Optimization , 1999, J. Heuristics.
[60] David E. Goldberg,et al. Hierarchical Bayesian Optimization Algorithm , 2006, Scalable Optimization via Probabilistic Modeling.
[61] P. Bosman,et al. IDEAs based on the normal kernels probability density function , 2000 .
[62] David E. Goldberg,et al. Influence of selection and replacement strategies on linkage learning in BOA , 2007, 2007 IEEE Congress on Evolutionary Computation.
[63] Petr Posík. Estimation of Distribution Algorithms , 2006 .
[64] David E. Goldberg,et al. Using Previous Models to Bias Structural Learning in the Hierarchical BOA , 2012, Evolutionary Computation.
[65] Pedro Larrañaga,et al. Mixtures of Kikuchi Approximations , 2006, ECML.
[66] Siddhartha Shakya,et al. An EDA based on local markov property and gibbs sampling , 2008, GECCO '08.
[67] Changjiu Zhou,et al. Biped gait optimization using spline function based probability model , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..
[68] Alexander Mendiburu,et al. Parallel EDAs to create multivariate calibration models for quantitative chemical applications , 2006, J. Parallel Distributed Comput..
[69] Pedro Larrañaga,et al. Protein Folding in Simplified Models With Estimation of Distribution Algorithms , 2008, IEEE Transactions on Evolutionary Computation.
[70] Matthew O. Ward,et al. A Taxonomy of Glyph Placement Strategies for Multidimensional Data Visualization , 2002, Inf. Vis..
[71] Steffen L. Lauritzen,et al. Graphical models in R , 1996 .
[72] William E. Hart,et al. Fast Protein Folding in the Hydrophobic-Hydrophillic Model within Three-Eights of Optimal , 1996, J. Comput. Biol..
[73] Siddhartha Shakya,et al. Optimization by estimation of distribution with DEUM framework based on Markov random fields , 2007, Int. J. Autom. Comput..
[74] Roberto Santana,et al. Estimation of Distribution Algorithms with Kikuchi Approximations , 2005, Evolutionary Computation.
[75] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[76] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[77] William E. Hart,et al. Protein structure prediction with evolutionary algorithms , 1999 .
[78] Maria E. Orlowska,et al. Finding the Optimal Path in 3D Spaces Using EDAs - The Wireless Sensor Networks Scenario , 2007, ICANNGA.
[79] Carlos Cotta,et al. Protein Structure Prediction Using Evolutionary Algorithms Hybridized with Backtracking , 2009, IWANN.
[80] Dirk Thierens,et al. Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The IDEA , 2000, PPSN.
[81] B. Everitt,et al. Finite Mixture Distributions , 1981 .
[82] K. Dill. Theory for the folding and stability of globular proteins. , 1985, Biochemistry.