Graphical models for machine learning and digital communication
Graphical models for machine learning and digital communication
Learning in graphical models
Schemata, Distributions and Graphical Models in Evolutionary Optimization
Journal of Heuristics
RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
From Recombination of Genes to the Estimation of Distributions I. Binary Parameters
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
The science of breeding and its application to the breeder genetic algorithm (bga)
Evolutionary Computation
Evolutionary induction of sparse neural trees
Evolutionary Computation
The equation for response to selection and its use for prediction
Evolutionary Computation
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
A Survey of Optimization by Building and Using Probabilistic Models
Computational Optimization and Applications
Schemata, Distributions and Graphical Models in Evolutionary Optimization
Journal of Heuristics
Evolutionary computation and Wright's equation
Theoretical Computer Science - Natural computing
Optimal Mutation Rate Using Bayesian Priors for Estimation of Distribution Algorithms
SAGA '01 Proceedings of the International Symposium on Stochastic Algorithms: Foundations and Applications
Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The IDEA
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
A Factorized Distribution Algorithm Using Single Connected Bayesian Networks
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Bayesian Evolutionary Optimization Using Helmholtz Machines
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Permutation Optimization by Iterated Estimation of Random Keys Marginal Product Factorizations
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
A unified Bayesian framework for evolutionary learning and optimization
Advances in evolutionary computing
From theory to practice: an evolutionary algorithm for the antenna placement problem
Advances in evolutionary computing
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Using a Markov network model in a univariate EDA: an empirical cost-benefit analysis
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Exploiting gradient information in numerical multi--objective evolutionary optimization
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
On the complexity of hierarchical problem solving
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Approximate factorizations of distributions and the minimum relative entropy principle
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
A generator for hierarchical problems
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Gene Expression and Fast Construction of Distributed Evolutionary Representation
Evolutionary Computation
The Estimation of Distributions and the Minimum Relative Entropy Principle
Evolutionary Computation
Convergence Time for the Linkage Learning Genetic Algorithm
Evolutionary Computation
The correlation-triggered adaptive variance scaling IDEA
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Combining gradient techniques for numerical multi-objective evolutionary optimization
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Linkage identification by fitness difference clustering
Evolutionary Computation
Adaptive variance scaling in continuous multi-objective estimation-of-distribution algorithms
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Sporadic model building for efficiency enhancement of the hierarchical BOA
Genetic Programming and Evolvable Machines
Detecting the epistatic structure of generalized embedded landscape
Genetic Programming and Evolvable Machines
Wrapper discretization by means of estimation of distribution algorithms
Intelligent Data Analysis
Optimal query complexity bounds for finding graphs
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
iBOA: the incremental bayesian optimization algorithm
Proceedings of the 10th annual conference on Genetic and evolutionary computation
BAIS: A Bayesian Artificial Immune System for the effective handling of building blocks
Information Sciences: an International Journal
Cooperative coevolution and univariate estimation of distribution algorithms
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms
Combinatorial effects of local structures and scoring metrics in bayesian optimization algorithm
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
EDA-RL: estimation of distribution algorithms for reinforcement learning problems
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Analysis of evolutionary algorithms on the one-dimensional spin glass with power-law interactions
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Lower and upper bounds for linkage discovery
IEEE Transactions on Evolutionary Computation
A fully multivariate DEUM algorithm
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Estimation of distribution algorithm based on copula theory
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Analyzing the probability of the optimum in EDAs based on Bayesian networks
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Analyzing probabilistic models in hierarchical BOA
IEEE Transactions on Evolutionary Computation - Special issue on evolutionary algorithms based on probabilistic models
Design of multithreaded estimation of distribution algorithms
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Pruning neural networks with distribution estimation algorithms
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Optimal query complexity bounds for finding graphs
Artificial Intelligence
A framework for estimation of distribution algorithms based on maximum entropy
ICNC'09 Proceedings of the 5th international conference on Natural computation
Research frontier: linkage discovery through data mining
IEEE Computational Intelligence Magazine
Multivariate multi-model approach for globally multimodal problems
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Rule acquisition for cognitive agents by using estimation of distribution algorithms
International Journal of Knowledge Engineering and Soft Data Paradigms
Sensibility of linkage information and effectiveness of estimated distributions
Evolutionary Computation
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Idealized dynamic population sizing for uniformly scaled problems
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Almost tight upper bound for finding Fourier coefficients of bounded pseudo-Boolean functions
Journal of Computer and System Sciences
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part I
Combinatorial optimization by learning and simulation of Bayesian networks
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Estimation of distribution algorithms with mutation
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
An evolutionary approach for solving the rubik's cube incorporating exact methods
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Estimation of particle swarm distribution algorithms: Combining the benefits of PSO and EDAs
Information Sciences: an International Journal
A Markovianity based optimisation algorithm
Genetic Programming and Evolvable Machines
A review on probabilistic graphical models in evolutionary computation
Journal of Heuristics
International Journal of Applied Metaheuristic Computing
International Journal of Applied Metaheuristic Computing
Benchmarking parameter-free amalgam on functions with and without noise
Evolutionary Computation
On the taxonomy of optimization problems under estimation of distribution algorithms
Evolutionary Computation
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The Factorized Distribution Algorithm (FDA) is an evolutionary algorithm which combines mutation and recombination by using a distribution. The distribution is estimated from a set of selected points. In general, a discrete distribution defined for n binary variables has 2n parameters. Therefore it is too expensive to compute. For additively decomposed discrete functions (ADFs) there exist algorithms which factor the distribution into conditional and marginal distributions. This factorization is used by FDA. The scaling of FDA is investigated theoretically and numerically. The scaling depends on the ADF structure and the specific assignment of function values. Difficult functions on a chain or a tree structure are solved in about O(n√n) operations. More standard genetic algorithms are not able to optimize these functions. FDA is not restricted to exact factorizations. It also works for approximate factorizations as is shown for a circle and a grid structure. By using results from Bayes networks, FDA is extended to LFDA. LFDA computes an approximate factorization using only the data, not the ADF structure. The scaling of LFDA is compared to the scaling of FDA.