Mateda-2.0: Estimation of Distribution Algorithms in MATLAB

Partially supported by the Saiotek and Research Groups 2007-2012 (IT-242-07) programs (Basque Government), TIN2008-06815-C02-01, TIN- 2008-06815-C02-02, TIN2007-62626 and Consolider Ingenio 2010 - CSD2007-00018 projects (Spanish Ministry of Science and Innovation), the CajalBlueBrain project, and the COMBIOMED network in computational biomedicine (Carlos III Health Institute).

[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.

[56]  李幼升,et al.  Ph , 1989 .

[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.