Bayesian Optimization Algorithm: From Single Level to Hierarchy
暂无分享,去创建一个
[1] David Maxwell Chickering,et al. Learning Bayesian Networks: The Combination of Knowledge and Statistical Data , 1994, Machine Learning.
[2] Gregory F. Cooper,et al. A Bayesian method for the induction of probabilistic networks from data , 1992, Machine Learning.
[3] David E. Goldberg,et al. Combining The Strengths Of Bayesian Optimization Algorithm And Adaptive Evolution Strategies , 2002, GECCO.
[4] David E. Goldberg,et al. From Twomax To The Ising Model: Easy And Hard Symmetrical Problems , 2002, GECCO.
[5] Elena Marchiori,et al. Evolutionary Algorithms for the Satisfiability Problem , 2002, Evolutionary Computation.
[6] David E. Goldberg,et al. The Design of Innovation: Lessons from and for Competent Genetic Algorithms , 2002 .
[7] Jiri Ocenasek,et al. EXPERIMENTAL STUDY: HYPERGRAPH PARTITIONING BASED ON THE SIMPLE AND ADVANCED GENETIC ALGORITHM BMDA AND BOA , 2002 .
[8] J. A. Lozano,et al. Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation , 2001 .
[9] Dirk Thierens,et al. Multi-objective mixture-based iterated density estimation evolutionary algorithms , 2001 .
[10] Thomas D. LaToza,et al. On the supply of building blocks , 2001 .
[11] David E. Goldberg,et al. Bayesian optimization algorithm, decision graphs, and Occam's razor , 2001 .
[12] D. Goldberg,et al. Verification and extension of the theory of global-local hybrids , 2001 .
[13] D. Goldberg,et al. Escaping hierarchical traps with competent genetic algorithms , 2001 .
[14] D. Goldberg,et al. Don't evaluate, inherit , 2001 .
[15] C. V. Hoyweghen. Detecting spin-flip symmetry in optimization problems , 2001 .
[16] Erick Cantú-Paz,et al. Supervised and unsupervised discretization methods for evolutionary algorithms , 2001 .
[17] Erick Cantú-Paz,et al. Efficient and Accurate Parallel Genetic Algorithms , 2000, Genetic Algorithms and Evolutionary Computation.
[18] L. Kallel,et al. Theoretical Aspects of Evolutionary Computing , 2001, Natural Computing Series.
[19] Franz Rothlauf,et al. Towards a theory of representations for genetic and evolutionary algorithms - development of basic concepts and their application to binary and tree representations , 2001, Ausgezeichnete Informatikdissertationen.
[20] Kalyanmoy Deb,et al. Multi-objective optimization using evolutionary algorithms , 2001, Wiley-Interscience series in systems and optimization.
[21] W. Langdon,et al. Analysis of Schema Variance and Short Term Extinction Likelihoods , 2001 .
[22] Dirk Thierens,et al. Exploiting gradient information in continuous iterated density estimation evolutionary algorithms , 2001 .
[23] John H. Holland,et al. Building Blocks, Cohort Genetic Algorithms, and Hyperplane-Defined Functions , 2000, Evolutionary Computation.
[24] David E. Goldberg,et al. Genetic Algorithms, Clustering, and the Breaking of Symmetry , 2000, PPSN.
[25] David E. Goldberg,et al. Linkage Problem, Distribution Estimation, and Bayesian Networks , 2000, Evolutionary Computation.
[26] David E. Goldberg,et al. Time Complexity of genetic algorithms on exponentially scaled problems , 2000, GECCO.
[27] David E. Goldberg,et al. Bayesian Optimization Algorithm, Population Sizing, and Time to Convergence , 2000, GECCO.
[28] Franz Rothlauf,et al. Bad Codings and the Utility of Well-Designed Genetic Algorithms , 2000, GECCO.
[29] Pedro Larrañaga,et al. Combinatonal Optimization by Learning and Simulation of Bayesian Networks , 2000, UAI.
[30] Pedro Larrañaga,et al. Optimization in Continuous Domains by Learning and Simulation of Gaussian Networks , 2000 .
[31] Josef Schwarz,et al. The Parallel Bayesian Optimization Algorithm , 2000 .
[32] Fernando G. Lobo,et al. A Survey of Optimization by Building and Using Probabilistic Models , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).
[33] J. A. Lozano,et al. Analyzing the PBIL Algorithm by Means of Discrete Dynamical Systems , 2000 .
[34] P. Bosman,et al. Continuous iterated density estimation evolutionary algorithms within the IDEA framework , 2000 .
[35] Heinz Mühlenbein,et al. FDA -A Scalable Evolutionary Algorithm for the Optimization of Additively Decomposed Functions , 1999, Evolutionary Computation.
[36] Andrew W. Moore,et al. Bayesian networks for lossless dataset compression , 1999, KDD '99.
[37] Toby Walsh,et al. Morphing: Combining Structure and Randomness , 1999, AAAI/IAAI.
[38] David E. Goldberg. Using Time Efficiently: Genetic-Evolutionary Algorithms and the Continuation Problem , 1999, GECCO.
[39] Dirk Thierens,et al. Linkage Information Processing In Distribution Estimation Algorithms , 1999, GECCO.
[40] Marcus Gallagher,et al. Real-valued Evolutionary Optimization using a Flexible Probability Density Estimator , 1999, GECCO.
[41] David E. Goldberg,et al. Optimizing Global-Local Search Hybrids , 1999, GECCO.
[42] Fernando G. Lobo,et al. A parameter-less genetic algorithm , 1999, GECCO.
[43] D. Goldberg,et al. BOA: the Bayesian optimization algorithm , 1999 .
[44] Heinz Mühlenbein,et al. Schemata, Distributions and Graphical Models in Evolutionary Optimization , 1999, J. Heuristics.
[45] Martin Loebl,et al. On the Theory of Pfaffian Orientations. I. Perfect Matchings and Permanents , 1998, Electron. J. Comb..
[46] Martin Loebl,et al. On the Theory of Pfaffian Orientations. II. T-joins, k-cuts, and Duality of Enumeration , 1998, Electron. J. Comb..
[47] E. Cantu-Paz,et al. The Gambler's Ruin Problem, Genetic Algorithms, and the Sizing of Populations , 1997, Evolutionary Computation.
[48] M. Pelikán,et al. The Bivariate Marginal Distribution Algorithm , 1999 .
[49] David E. Goldberg,et al. Probabilistic Crowding: Deterministic Crowding with Probabilistic Replacement , 1999 .
[50] P. Grünwald. The Minimum Description Length Principle and Reasoning under Uncertainty , 1998 .
[51] Michèle Sebag,et al. Extending Population-Based Incremental Learning to Continuous Search Spaces , 1998, PPSN.
[52] Jan Naudts,et al. The Effect of Spin-Flip Symmetry on the Performance of the Simple GA , 1998, PPSN.
[53] L. Darrell Whitley,et al. Genetic Algorithm Behavior in the MAXSAT Domain , 1998, PPSN.
[54] Jordan B. Pollack,et al. Modeling Building-Block Interdependency , 1998, PPSN.
[55] Rafal Salustowicz,et al. H-PIPE: Facilitating Hierarchical Program Evolution through Skip Nodes , 1998 .
[56] Shumeet Baluja,et al. Fast Probabilistic Modeling for Combinatorial Optimization , 1998, AAAI/IAAI.
[57] D. Goldberg,et al. Domino convergence, drift, and the temporal-salience structure of problems , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).
[58] David E. Goldberg,et al. The compact genetic algorithm , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).
[59] Jorma Rissanen,et al. Stochastic Complexity in Statistical Inquiry , 1989, World Scientific Series in Computer Science.
[60] Louise Travé-Massuyès,et al. Telephone Network Traffic Overloading Diagnosis and Evolutionary Computation Techniques , 1997, Artificial Evolution.
[61] Heinz Mühlenbein,et al. The Equation for Response to Selection and Its Use for Prediction , 1997, Evolutionary Computation.
[62] Chu Min Li,et al. Heuristics Based on Unit Propagation for Satisfiability Problems , 1997, IJCAI.
[63] David Maxwell Chickering,et al. A Bayesian Approach to Learning Bayesian Networks with Local Structure , 1997, UAI.
[64] Rafal Salustowicz,et al. Probabilistic Incremental Program Evolution , 1997, Evolutionary Computation.
[65] Jürgen Schmidhuber,et al. Probabilistic Incremental Program Evolution: Stochastic Search Through Program Space , 1997, ECML.
[66] G. Harik. Learning gene linkage to efficiently solve problems of bounded difficulty using genetic algorithms , 1997 .
[67] S. Baluja,et al. Using Optimal Dependency-Trees for Combinatorial Optimization: Learning the Structure of the Search Space , 1997 .
[68] Paul A. Viola,et al. MIMIC: Finding Optima by Estimating Probability Densities , 1996, NIPS.
[69] H. Kargupta. Search, polynomial complexity, and the fast messy genetic algorithm , 1996 .
[70] H. Mühlenbein,et al. From Recombination of Genes to the Estimation of Distributions I. Binary Parameters , 1996, PPSN.
[71] G. Rinaldi,et al. Exact ground states of two-dimensional ±J Ising spin glasses , 1996 .
[72] David Heckerman,et al. Asymptotic Model Selection for Directed Networks with Hidden Variables , 1996, UAI.
[73] Nir Friedman,et al. On the Sample Complexity of Learning Bayesian Networks , 1996, UAI.
[74] Nir Friedman,et al. Learning Bayesian Networks with Local Structure , 1996, UAI.
[75] David E. Goldberg,et al. Genetic Algorithms, Selection Schemes, and the Varying Effects of Noise , 1996, Evolutionary Computation.
[76] David Heckerman,et al. Knowledge Representation and Inference in Similarity Networks and Bayesian Multinets , 1996, Artif. Intell..
[77] Jorma Rissanen,et al. Fisher information and stochastic complexity , 1996, IEEE Trans. Inf. Theory.
[78] Melanie Mitchell,et al. An introduction to genetic algorithms , 1996 .
[79] Nikolaus Hansen,et al. On the Adaptation of Arbitrary Normal Mutation Distributions in Evolution Strategies: The Generating Set Adaptation , 1995, ICGA.
[80] Lawrence K. Saul,et al. The 2D±J Ising spin glass: exact partition functions in polynomial time , 1994 .
[81] Dirk Thierens,et al. Convergence Models of Genetic Algorithm Selection Schemes , 1994, PPSN.
[82] Heinz Mühlenbein,et al. On the Mean Convergence Time of Evolutionary Algorithms without Selection and Mutation , 1994, PPSN.
[83] John R. Koza,et al. Genetic programming 2 - automatic discovery of reusable programs , 1994, Complex adaptive systems.
[84] Simon Handley,et al. On the use of a directed acyclic graph to represent a population of computer programs , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.
[85] Shumeet Baluja,et al. A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning , 1994 .
[86] Dirk Thierens,et al. Mixing in Genetic Algorithms , 1993, ICGA.
[87] Peter J. Fleming,et al. Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization , 1993, ICGA.
[88] Jeffrey Horn,et al. Finite Markov Chain Analysis of Genetic Algorithms with Niching , 1993, ICGA.
[89] Colin R. Reeves,et al. Using Genetic Algorithms with Small Populations , 1993, ICGA.
[90] Heinz Mühlenbein,et al. Predictive Models for the Breeder Genetic Algorithm I. Continuous Parameter Optimization , 1993, Evolutionary Computation.
[91] John R. Koza,et al. Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.
[92] Hector J. Levesque,et al. A New Method for Solving Hard Satisfiability Problems , 1992, AAAI.
[93] Kalyanmoy Deb,et al. Analyzing Deception in Trap Functions , 1992, FOGA.
[94] Heinz Mühlenbein,et al. How Genetic Algorithms Really Work: Mutation and Hillclimbing , 1992, PPSN.
[95] Kalyanmoy Deb,et al. Genetic Algorithms, Noise, and the Sizing of Populations , 1992, Complex Syst..
[96] Samir W. Mahfoud. Crowding and Preselection Revisited , 1992, PPSN.
[97] Joseph Culberson,et al. Genetic Invariance: A New Paradigm for Genetic Algorithm Design , 1992 .
[98] Peter C. Cheeseman,et al. Where the Really Hard Problems Are , 1991, IJCAI.
[99] Yuval Davidor,et al. A Naturally Occurring Niche and Species Phenomenon: The Model and First Results , 1991, ICGA.
[100] David E. Goldberg,et al. Genetic Algorithms and the Variance of Fitness , 1991, Complex Syst..
[101] Melanie Mitchell,et al. The royal road for genetic algorithms: Fitness landscapes and GA performance , 1991 .
[102] David R. Jefferson,et al. Selection in Massively Parallel Genetic Algorithms , 1991, ICGA.
[103] Heinz Mühlenbein,et al. Evolution in Time and Space - The Parallel Genetic Algorithm , 1990, FOGA.
[104] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[105] David E. Goldberg,et al. Sizing Populations for Serial and Parallel Genetic Algorithms , 1989, ICGA.
[106] Martina Gorges-Schleuter,et al. ASPARAGOS An Asynchronous Parallel Genetic Optimization Strategy , 1989, ICGA.
[107] Kalyanmoy Deb,et al. An Investigation of Niche and Species Formation in Genetic Function Optimization , 1989, ICGA.
[108] Ivan Hal Sudborough,et al. Min cut is NP-complete for edge weighted trees , 1988 .
[109] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[110] David E. Goldberg,et al. Finite Markov Chain Analysis of Genetic Algorithms , 1987, ICGA.
[111] David E. Goldberg,et al. Genetic Algorithms with Sharing for Multimodalfunction Optimization , 1987, ICGA.
[112] Dana S. Richards,et al. Punctuated Equilibria: A Parallel Genetic Algorithm , 1987, ICGA.
[113] David H. Ackley,et al. An empirical study of bit vector function optimization , 1987 .
[114] J. E. Baker. Adaptive Selection Methods for Genetic Algorithms , 1985, ICGA.
[115] Paul Bryant Grosso,et al. Computer Simulations of Genetic Adaptation: Parallel Subcomponent Interaction in a Multilocus Model , 1985 .
[116] Michael L. Mauldin,et al. Maintaining Diversity in Genetic Search , 1984, AAAI.
[117] Z. A. Perry. Experimental study of speciation in ecological niche theory using genetic algorithms , 1984 .
[118] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.
[119] Lashon B. Booker,et al. Intelligent Behavior as an Adaptation to the Task Environment , 1982 .
[120] J. Rissanen,et al. Modeling By Shortest Data Description* , 1978, Autom..
[121] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[122] L. A. Marascuilo,et al. Nonparametric and Distribution-Free Methods for the Social Sciences , 1977 .
[123] Kenneth Alan De Jong,et al. An analysis of the behavior of a class of genetic adaptive systems. , 1975 .
[124] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[125] John H. Holland,et al. Genetic Algorithms and the Optimal Allocation of Trials , 1973, SIAM J. Comput..
[126] Ingo Rechenberg,et al. Evolutionsstrategie : Optimierung technischer Systeme nach Prinzipien der biologischen Evolution , 1973 .
[127] D. J. Cavicchio,et al. Adaptive search using simulated evolution , 1970 .
[128] Herbert A. Simon,et al. The Sciences of the Artificial , 1970 .
[129] C. N. Liu,et al. Approximating discrete probability distributions with dependence trees , 1968, IEEE Trans. Inf. Theory.
[130] S. Wright. Evolution And The Genetics Of Populations : A Treatise , 1968 .
[131] Donald W. Loveland,et al. A machine program for theorem-proving , 2011, CACM.
[132] R. Prim. Shortest connection networks and some generalizations , 1957 .
[133] R. A. Leibler,et al. On Information and Sufficiency , 1951 .
[134] W. Feller. An Introduction to Probability Theory and Its Applications , 1959 .