M. Pelikán

发表

Escaping hierarchical traps with competent genetic algorithms

D. Goldberg, M. Pelikán, 2001 .

Don't evaluate, inherit

D. Goldberg, M. Pelikán, K. Sastry, 2001 .

BOA: the Bayesian optimization algorithm

D. Goldberg, M. Pelikán, E. Cantú-Paz, 1999 .

The Bivariate Marginal Distribution Algorithm

M. Pelikán, Heinz Muehlenbein, 1999 .

A Survey of Optimization by Building and Using Probabilistic Models

David E. Goldberg, Martin Pelikan, Fernando G. Lobo, 2002, Comput. Optim. Appl..

Bayesian optimization algorithm, decision graphs, and Occam's razor

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2001 .

A Survey of Optimization by Building and Using Probabilistic Models

Fernando G. Lobo, D. Goldberg, M. Pelikán, 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

Linkage Problem, Distribution Estimation, and Bayesian Networks

David E. Goldberg, Martin Pelikan, Erick Cantú-Paz, 2000, Evolutionary Computation.

Scalability of the Bayesian optimization algorithm

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2002, Int. J. Approx. Reason..

Introduction to Estimation of Distribution Algorithms

Fernando G. Lobo, M. Pelikán, F. Lobo, 2012 .

iBOA: the incremental bayesian optimization algorithm

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2008, GECCO '08.

Getting the best of both worlds: Discrete and continuous genetic and evolutionary algorithms in concert

David E. Goldberg, Martin Pelikan, Shigeyoshi Tsutsui, 2003, Inf. Sci..

Analyzing the evolutionary pressures in XCS

M. Pelikán, Martin Volker Butz, 2001 .

Limits of scalability of multiobjective estimation of distribution algorithms

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2005, 2005 IEEE Congress on Evolutionary Computation.

Effects of a deterministic hill climber on hBOA

David E. Goldberg, Martin Pelikan, Elizabeth Radetic, 2009, GECCO.

Multiobjective Estimation of Distribution Algorithms

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2006, Scalable Optimization via Probabilistic Modeling.

Extracted global structure makes local building block processing effective in XCS

Martin V. Butz, Xavier Llorà, David E. Goldberg, 2005, GECCO '05.

GECCO 2007: Genetic and Evolutionary Computation Conference

Thomas Stützle, Riccardo Poli, Mauro Birattari, 2007 .

Sporadic model building for efficiency enhancement of hierarchical BOA

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2006, GECCO.

Research on the Bayesian Optimization Algorithm Research on the Bayesian Optimization Algorithm

D. Goldberg, M. Pelikán, 2022 .

Influence of selection and replacement strategies on linkage learning in BOA

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2007, 2007 IEEE Congress on Evolutionary Computation.

Population Sizing for Entropy-based Model Building in Genetic Algorithms

D. Goldberg, M. Pelikán, K. Sastry, 2006 .

Decomposable Problems, Niching, and Scalability of Multiobjective Estimation of Distribution Algorithms pdf

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2005, ArXiv.

Structure and flexibility within proteins as identified through small angle X-ray scattering.

Greg L. Hura, M. Pelikán, M. Hammel, 2009, General physiology and biophysics.

Ku and DNA-dependent Protein Kinase Dynamic Conformations and Assembly Regulate DNA Binding and the Initial Non-homologous End Joining Complex*

Martin Pelikan, John A. Tainer, Greg L. Hura, 2009, The Journal of Biological Chemistry.

Genetic Algorithms

M. Pelikán, 2010 .

Database independent detection of isotopically labeled MS/MS spectrum peptide pairs.

Martin Pelikan, Jiri Ocenasek, Ralph Schlapbach, 2005, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

Sporadic Model Building for Efficiency Enhancement of hBOA Martin Pelikan

D. Goldberg, M. Pelikán, 2005 .

Learn from the Past : Improving Model-Directed Optimization by Transfer Learning Based on Distance-Based Bias

M. Pelikán, Mark Hauschild, 2012 .

Evolutionary Algorithm Using Marginal Histogram Models in Continuous Domain

D. Goldberg, M. Pelikán, S. Tsutsui, 2007 .

Practical , Robust , and Scalable Black-Box Optimization with BOA and hBOA

M. Pelikán, 2022 .

Cunning Ant System : An Extension of Edge Histogram Sampling Algorithms to ACO

M. Pelikán, S. Tsutsui, 2006 .

Node Histogram vs . Edge Histogram : A Comparison of PMBGAs in Permutation Domains

David E. Goldberg, Martin Pelikan, Shigeyoshi Tsutsui, 2006 .

Finding ground states of Sherrington-Kirkpatrick spin glasses with hierarchical boa and genetic algorithms

Martin Pelikan, Helmut G. Katzgraber, Sigismund Kobe, 2008, GECCO '08.

Use of genetic algorithms with multivariate regression for determination of gelatine in historic papers based on FT-IR and NIR spectral data.

J Kolar, M Strlic, M. Pelikán, 2010, Talanta.

Effect of Local Search on Edge Histogram Based Sampling Algorithms for Permutation Problems

M. Pelikán, S. Tsutsui, Ashish Ghosh, 2005 .

Solving Sequence Problems by Building and Sampling Edge Histograms

David E. Goldberg, Martin Pelikan, Shigeyoshi Tsutsui, 2002 .

A Survey of Estimation of Distribution Algorithms

M. Pelikán, Mark Hauschild, 2011 .

Boa for Nurse Scheduling Li J and Aickelin U (2006): 'bayesian Optimisation Algorithm for Nurse Scheduling', Scalable Optimization via Probabilistic Modeling: from Algorithms to Applications (studies in Computational Intelligence), Edited

M. Pelikán, K. Sastry, U. Aickelin, 2007 .

Eeciency Enhancement of Probabilistic Model Building Genetic Algorithms Eeciency Enhancement of Probabilistic Model Building Genetic Algorithms

D. Goldberg, M. Pelikán, K. Sastry, 2022 .

New businesses for small and medium entrepreneurs (SMEs) in the Renewable Energy Sources (RES)

M. Pelikán, J. Havlíček, T. Subrt, 2018 .

Bayesian Optimization Algorithm: From Single Level to Hierarchy

David E. Goldberg, Martin Pelikan, D. Goldberg, 2002 .

From Genetic Variation to Probabilistic Modeling

Martin Pelikan, M. Pelikán, 2005 .

The Challenge of Hierarchical Difficulty

Martin Pelikan, M. Pelikán, 2005 .

Genetic and Evolutionary Computation Conference, GECCO 2010, Proceedings, Portland, Oregon, USA, July 7-11, 2010, Companion Material

Martin Pelikan, Jrgen Branke, M. Pelikán, 2010, GECCO.

Marginal Distributions in Evolutionary Algorithms

Martin Pelikan, Heinz Muehlenbein, M. Pelikán, 2007 .

Probabilistic model-building genetic algorithms

Martin Pelikan, M. Pelikán, 2011 .

Multiple-objective Bayesian Optimization Algorithm

David E. Goldberg, Martin Pelikan, Nazan Khan, 2002, GECCO.

Design of Parallel Estimation of Distribution Algorithms

Martin Pelikan, Erick Cantú-Paz, Jiri Ocenasek, 2006, Scalable Optimization via Probabilistic Modeling.

Effective and Reliable Online Classification Combining XCS with EDA Mechanisms

Martin V. Butz, Xavier Llorà, David E. Goldberg, 2006, Scalable Optimization via Probabilistic Modeling.

A generalized model for quantifying the impact of Ambient Intelligence on smart workplaces: Applications in manufacturing

Martin Pelikan, Shady Aly, Ivan Vrana, 2014, J. Ambient Intell. Smart Environ..

Genetic and Evolutionary Computation Conference, GECCO 2010, Proceedings, Portland, Oregon, USA, July 7-11, 2010

Martin Pelikan, Jrgen Branke, M. Pelikán, 2010, GECCO.

Parameter-less Hierarchical Bayesian Optimization Algorithm

Martin Pelikan, Alexander K. Hartmann, Tz-Kai Lin, 2007, Parameter Setting in Evolutionary Algorithms.

BOA for Nurse Scheduling Optimisation Algorithm for Scheduling', Scalable Optimization via

M. Pelikán, K. Sastry, U. Aickelin, 2007 .

Dreams of the future: an examination of Czech and Irish tertiary level students intention to be an entrepreneur

M. Pelikán, J. Havlíček, N. Birdthistle, 2014 .

Genetic and Evolutionary Computation Conference 2008 : GECCO 2008

Julian F. Miller, Giuliano Antoniol, Maarten Keijzer, 2008, GECCO 2008.

Dependency Structure Matrix, Genetic Algorithms, and Effective Recombination

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2009, Evolutionary Computation.

Empirical analysis of ideal recombination on random decomposable problems

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2007, GECCO '07.

Population sizing for entropy-based model building in discrete estimation of distribution algorithms

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2007, GECCO '07.

Efficiency Enhancement of Estimation of Distribution Algorithms

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2006, Scalable Optimization via Probabilistic Modeling.

Efficiency enhancement of genetic algorithms via building-block-wise fitness estimation

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

Evaluation-Relaxation Schemes for Genetic and Evolutionary Algorithms

Franz Rothlauf, Martin Pelikan, Kumara Sastry, 2004 .

Estimation of Distribution Algorithms

Martin Pelikan, Fernando G. Lobo, Mark Hauschild, 2015, Handbook of Computational Intelligence.

Initial-population bias in the univariate estimation of distribution algorithm

Martin Pelikan, Kumara Sastry, M. Pelikán, 2009, GECCO.

Multi-agent System in Smart Econometric Environment

Ivan Vrana, Jan Tyrychtr, Martin Pelikán, 2019, Intelligent Systems Applications in Software Engineering.

Linkage Learning Accuracy in the Bayesian Optimization Algorithm

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2008, Linkage in Evolutionary Computation.

Hierarchical BOA, Cluster Exact Approximation, and Ising Spin Glasses

Martin Pelikan, Kumara Sastry, Alexander K. Hartmann, 2006, PPSN.

Automated Global Structure Extraction for Effective Local Building Block Processing in XCS

Martin V. Butz, Xavier Llorà, David E. Goldberg, 2006, Evolutionary Computation.

Genetic Programming, Probabilistic Incremental Program Evolution, and Scalability

Martin Pelikan, Kumara Sastry, Radovan Ondas, 2006 .

Searching for Ground States of Ising Spin Glasses with Hierarchical BOA and Cluster Exact Approximation

Martin Pelikan, Alexander K. Hartmann, M. Pelikán, 2006, Scalable Optimization via Probabilistic Modeling.

Mechanism of DNA substrate recognition by the mammalian DNA repair enzyme, Polynucleotide Kinase

M. Pelikán, J. Tainer, J. Glover, 2009, Nucleic acids research.

Performance of Evolutionary Algorithms on Random Decomposable Problems

Martin V. Butz, David E. Goldberg, Martin Pelikan, 2006, PPSN.

Model accuracy in the Bayesian optimization algorithm

David E. Goldberg, Martin Pelikan, Cláudio F. Lima, 2011, Soft Comput..

From mating pool distributions to model overfitting

Martin Pelikan, Cláudio F. Lima, Fernando G. Lobo, 2008, GECCO '08.

Spurious dependencies and EDA scalability

Martin Pelikan, Elizabeth Radetic, M. Pelikán, 2010, GECCO '10.

Reducing Permission Requests in Mobile Apps

Pauline Anthonysamy, Nina Taft, Sai Teja Peddinti, 2019, Internet Measurement Conference.

An introduction and survey of estimation of distribution algorithms

Martin Pelikan, Mark Hauschild, M. Pelikán, 2011, Swarm Evol. Comput..

Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications (Studies in Computational Intelligence)

Martin Pelikan, Kumara Sastry, Erick Cantú-Paz, 2006 .

Performance of Network Crossover on NK Landscapes and Spin Glasses

Martin Pelikan, Mark Hauschild, M. Pelikán, 2010, PPSN.

Analysis of evolutionary algorithms on the one-dimensional spin glass with power-law interactions

Martin Pelikan, Helmut G. Katzgraber, M. Pelikán, 2009, GECCO.

Loopy Substructural Local Search for the Bayesian Optimization Algorithm

David E. Goldberg, Martin Pelikan, Cláudio F. Lima, 2009, SLS.

Hierarchical Bayesian Optimization Algorithm

David E. Goldberg, Martin Pelikan, D. Goldberg, 2006, Scalable Optimization via Probabilistic Modeling.

Hierarchical Problem Solving and the Bayesian Optimization Algorithm

David E. Goldberg, Martin Pelikan, D. Goldberg, 2000, GECCO.

Horizontal bridgman growth of gaas single crystals

M. Pelikán, F. Moravec, 1985 .

Performance of aggregation pheromone system on unimodal and multimodal problems

Martin Pelikan, Shigeyoshi Tsutsui, Ashish Ghosh, 2005, 2005 IEEE Congress on Evolutionary Computation.

Bayesian Optimization Algorithm

Martin Pelikan, M. Pelikán, 2005 .

A novel methodology for designing smart workplace environments utilizing fuzzy relations

Martin Pelikan, Shady Aly, Ivan Vrana, 2018, J. Ambient Intell. Smart Environ..

Substructural Neighborhoods for Local Search in the Bayesian Optimization Algorithm

Martin V. Butz, David E. Goldberg, Martin Pelikan, 2006, PPSN.

Multi-objective bayesian optimization algorithm

David E. Goldberg, Martin Pelikan, Nazan Khan, 2002 .

Genetic Algorithms, Clustering, and the Breaking of Symmetry

David E. Goldberg, Martin Pelikan, D. Goldberg, 2000, PPSN.

Influence of selection on structure learning in markov network EDAs: an empirical study

Martin Pelikan, John A. W. McCall, Alexander E. I. Brownlee, 2012, GECCO '12.

Transfer Learning, Soft Distance-Based Bias, and the Hierarchical BOA

Martin Pelikan, Pier Luca Lanzi, Mark W. Hauschild, 2012, PPSN.

Distance-based bias in model-directed optimization of additively decomposable problems pdf

Martin Pelikan, Mark Hauschild, M. Pelikán, 2012, GECCO '12.

Analysis of epistasis correlation on NK landscapes with nearest-neighbor interactions

Martin Pelikan, M. Pelikán, 2011, GECCO '11.

Analyzing Probabilistic Models in Hierarchical BOA

Martin Pelikan, Kumara Sastry, Cláudio F. Lima, 2009, IEEE Transactions on Evolutionary Computation.

Enhancing Efficiency of Hierarchical BOA Via Distance-Based Model Restrictions

Martin Pelikan, Mark Hauschild, M. Pelikán, 2008, PPSN.

1 KU AND DNA-DEPENDENT PROTEIN KINASE ( DNA-PK ) DYNAMIC CONFORMATIONS AND ASSEMBLY REGULATE DNA BINDING AND THE INITIAL NONHOMOLOGOUS END JOINING COMPLEX

Greg L. Hura, David J. Chen, M. Pelikán, 2009 .

Probabilistic model-building genetic algorithms

M. Pelikán, 2010, GECCO '10.

Parameter-Less Hierarchical BOA

Martin Pelikan, Tz-Kai Lin, M. Pelikán, 2004, GECCO.

Hierarchical Bayesian optimization algorithm: toward a new generation of evolutionary algorithms

Martin Pelikan, M. Pelikán, David E. Goldberg, 2010, SICE 2003 Annual Conference (IEEE Cat. No.03TH8734).

Fitness Inheritance in the Bayesian Optimization Algorithm

Martin Pelikan, Kumara Sastry, M. Pelikán, 2004, GECCO.

An application of a multivariate estimation of distribution algorithm to cancer chemotherapy

Martin Pelikan, John A. W. McCall, Alexander E. I. Brownlee, 2008, GECCO '08.

Intelligent bias of network structures in the hierarchical BOA

Martin Pelikan, Mark Hauschild, M. Pelikán, 2009, GECCO.

Using Previous Models to Bias Structural Learning in the Hierarchical BOA

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2008, Evolutionary Computation.

Analyzing probabilistic models in hierarchical BOA on traps and spin glasses

Martin Pelikan, Kumara Sastry, Cláudio F. Lima, 2007, GECCO '07.

Obtaining ground states of ising spin glasses via optimizing bonds instead of spins

Martin Pelikan, Alexander K. Hartmann, M. Pelikán, 2007, GECCO '07.

Order or not: does parallelization of model building in hBOA affect its scalability?

Martin Pelikan, James D. Laury, M. Pelikán, 2007, GECCO '07.

Sporadic model building for efficiency enhancement of hierarchical BOA

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2006, GECCO '06.

Computational Complexity and Simulation of Rare Events of Ising Spin Glasses

Martin Pelikan, Jiri Ocenasek, Matthias Troyer, 2004, GECCO.

Multiobjective hBOA, clustering, and scalability

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2005, GECCO '05.

c AS : The Cunning Ant System Solving the traveling salesman problem and the quadratic assignment problem using the cunning ant system

Martin Pelikan, Shigeyoshi Tsutsui, M. Pelikán, 2007 .

A hierarchy machine: Learning to optimize from nature and humans

David E. Goldberg, Martin Pelikan, D. Goldberg, 2003, Complex..

Time Complexity of genetic algorithms on exponentially scaled problems

David E. Goldberg, Martin Pelikan, Fernando G. Lobo, 2000, GECCO.

EM-OLAP Framework

Martin Pelikan, Hana Stiková, Ivan Vrana, 2018, Bus. Inf. Syst. Eng..

EM-OLAP Framework Econometric Model Transformation Method for OLAP Design in Intelligence Systems

M. Pelikán, I. Vrana, J. Tyrychtr, 2018 .

Hierarchical BOA Solves Ising Spin Glasses and MAXSAT

David E. Goldberg, Martin Pelikan, D. Goldberg, 2003, GECCO.

Dependency trees, permutations, and quadratic assignment problem

Martin Pelikan, Shigeyoshi Tsutsui, Rajiv Kalapala, 2007, GECCO '07.

Design of Multithreaded Estimation of Distribution Algorithms

Martin Pelikan, Jiri Ocenasek, Josef Schwarz, 2003, GECCO.

Population Expansion for Training Language Models with Private Federated Learning

M. Pelikán, Congzheng Song, Mona Chitnis, 2023, arXiv.org.

Sporadic model building for efficiency enhancement of the hierarchical BOA

D. Goldberg, M. Pelikán, K. Sastry, 2008, Genetic Programming and Evolvable Machines.

Scalability of genetic programming and probabilistic incremental program evolution pdf

Martin Pelikan, Kumara Sastry, Radovan Ondas, 2005, GECCO '05.

The Globalization of Higher Education – Be Responsible and Survive the Changes

Martin Pelikán, Jaroslav Havlicek, M. Pelikán, 2013 .

Hill Climbing with Learning (An Abstraction of Genetic Algorithm)

Martin Pelikan, Jiri Pospichal, Vladimír Kvasnička, 1995 .

Network crossover performance on NK landscapes and deceptive problems

Martin Pelikan, Mark Hauschild, M. Pelikán, 2010, GECCO '10.

Combining The Strengths Of Bayesian Optimization Algorithm And Adaptive Evolution Strategies

David E. Goldberg, Martin Pelikan, Shigeyoshi Tsutsui, 2002, GECCO.

How to reach a compromise solution on technical and non-structural flood control measures.

Ivan Vrana, Pavel Kovář, Martin Pelikán, 2018 .

Factor graph based factorization distribution algorithm

Martin Pelikan, Adel Torkaman Rahmani, B. Hoda Helmi, 2013, GECCO.

Linkage learning using the maximum spanning tree of the dependency graph

Martin Pelikan, Adel Torkaman Rahmani, B. Hoda Helmi, 2012, GECCO '12.

Automated Global Structure Extraction For Effective Local Building Block Processing in XCS

M. Pelikán, Martin Volker Butz, Xavier Llorà, 2005 .

Multi-objective bayesian optimization algorithm

D. Goldberg, M. Pelikán, Nazan Khan, 2002 .

Hybrid evolutionary algorithms on minimum vertex cover for random graphs

Martin Pelikan, Alexander K. Hartmann, Rajiv Kalapala, 2007, GECCO '07.