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Martin Pelikan: Publications

External links

Papers in Refereed Conference Proceedings, arXiv

Pelikan, M., Azam, S.S., Feldman, V., Silovsky, J., Talwar, K., Brinton, C., Likhomanenko, T. (2026). Enabling Differentially Private Federated Learning for Speech Recognition: Benchmarks, Adaptive Optimizers, and Gradient Clipping, NeurIPS 2026. [pdf] [arXiv.2310.00098]
Granqvist, F., Song, C., Cahill, A., van Dalen, R., Pelikan, M., Chan, Y. S., Feng, X., Krishnaswami, N., Jina, V., Chitnis, M. (2024). pfl-research: simulation framework for accelerating research in Private Federated Learning. [arXiv.2404.06430] [pdf] [github]
Pelikan, M., Azam, S.S., Feldman, V., Silovsky, J., Talwar, K., Likhomanenko, T. (2023). Federated Learning with Differential Privacy for End-to-End Speech Recognition, ICML 2024. [arXiv.2310.00098v1] [pdf]
Azam, S.S., Pelikan, M., Feldman, V., Talwar, K., Silovsky, J., Likhomanenko, T. (2023). Federated Learning for Speech Recognition: Revisiting Current Trends Towards Large-Scale ASR. International Workshop on Federated Learning in the Age of Foundation Models, NeurIPS 2023. [pdf] [presentation]
Azam, S.S., Likhomanenko, T., Pelikan, M., Silovsky, J. (2023). Importance of Smoothness Induced by Optimizers in FL4ASR: Towards Understanding Federated Learning for End-to-End ASR. In Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop (ASRU). [arxiv:2309.13102] [pdf]
Koga, T., Song, C., Pelikan, M., and Chitnis, M. (2023). Population Expansion for Training Language Models with Private Federated Learning. [arXiv:2307.07477] [pdf]
Peddinti, S.T., Bilogrevic, I., Taft, N., Pelikan, M., Erlingsson, U., Anthonysamy, P., and Hogben, G. (2019). Reducing permission requests in mobile apps. In Internet Measurement Conference (IMC 19), https://doi.org/10.1145/3355369.3355584. [pdf]
Pelikan, M., Hauschild, M. W. (2012). Distance-based bias in model-directed optimization of additively decomposable problems. ACM SIGEVO Genetic and Evolutionary Computation Con-ference (GECCO-2012), ACM Press, 273-280. [pdf]
Hauschild, M. W., Bhatia, S., Pelikan, M. (2012). Image Segmentation using a Genetic Algorithm and Hierarchical Local Search. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2012), ACM Press, 633-639. [pdf]
Brownlee, A., McCall, J., Pelikan, M. (2012). Influence of Selection on Structure Learning in Markov Network EDAs: An Empirical Study. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2012), ACM Press, 249-256. [pdf]
Pelikan, M., Hauschild, M.W., Lanzi, P.L. (2012). Transfer Learning, Soft Distance-Based Bias, and the Hierarchical BOA. In Parallel Problem Solving from Nature (PPSN-2012), 249-256. [pdf]
Pelikan, M. (2011). Analysis of Epistasis Correlation on NK Landscapes with Nearest-Neighbor Interactions. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2011), ACM Press, 1013-1020. [pdf]
Hauschild, M., Pelikan, M. (2011). Advanced Neighborhoods and Problem Difficulty Measures. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2011), ACM Press, 625-632. [pdf]
Pelikan, M., Hauschild, M., Thierens, D. (2011). Pairwise and Problem-Specific Distance Metrics in the Linkage Tree Genetic Algorithm. ACM SIGEVO Genetic and Evolutionary ComputationConference (GECCO-2011), ACM Press, 1005-1012. [pdf]
Pelikan, M. NK Landscapes, Problem Difficulty, and Hybrid Evolutionary Algorithms. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2010), 665-672. [pdf]
Radetic., E., Pelikan, M. Spurious Dependencies and EDA Scalability. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2010), 303-310. [pdf]
Hauschild, M., Pelikan, M. Network crossover performance on NK landscapes and deceptive problems. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2010), 665-672. [pdf]
Hauschild, M., Pelikan, M. (2010). Performance of Network Crossover on NK Landscapes and Spin Glasses. Parallel Problem Solving from Nature (PPSN XI), 462-471. [pdf]
Hauschild, M., Pelikan, M. (2009). Intelligent Bias of Network Structures in the Hierarchical BOA. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2009), 413-420. [pdf]
Pelikan, M., Katzgraber, H. (2009). Analysis of Evolutionary Algorithms on the One-Dimensional Spin Glass with Power-Law Interactions. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2009), 843-850. [pdf]
Radetic, E., Pelikan, M., Goldberg, D.E. (2009). Effects of a Deterministic Hill climber on hBOA. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2009), 437-444. [pdf]
Pelikan, M., Sastry, K., Goldberg, D.E., Butz, M.V., Hauschild, M. (2009). Performance of Evolutionary Algorithms on NK Landscapes with Nearest Neighbor Interactions and Tunable Overlap. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2009), 851-858. [pdf]
Pelikan, M., Sastry, K. (2009). Initial-Population Bias in the Univariate Estimation of Distribution Algorithm. Effects of a Deterministic Hill climber on hBOA. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2009), 429-436. [pdf]
Pelikan, M. (2008). Analysis of Estimation of Distribution Algorithms and Genetic Algorithms on NK Landscapes. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2008), 1033-1040. [pdf]
Pelikan, M., Sastry, K., Goldberg, D.E. (2008). iBOA: The Incremental Bayesian Optimization Algorithm. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2008), 455-462. [pdf]
Hauschild, M., Pelikan, M., Sastry, K., Goldberg, D.E. (2008). Using Previous Models to Bias Structural Learning in the Hierarchical BOA. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2008), 415-422. [pdf]
Pelikan, M., Katzgraber, H., Kobe, S. (2008). Finding Ground States of Sherrington-Kirkpatrick Spin Glasses with Hierarchical BOA and Genetic Algorithms. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2008), 447-454. [pdf]
Lima, C., Lobo, F., Pelikan, M. (2008). From Mating Pool Distributions to Model Overfitting. ACM SIGEVO Genetic and Evolutionary Computation Conf. (GECCO-2008), 431-438. [pdf]
Hauschild, M., Pelikan, M. (2008). Enhancing Efficiency of Hierarchical BOA via Distance-Based Model Restrictions. Parallel Problem Solving from Nature (PPSN X), 417-427. [pdf]
Hauschild, M., Pelikan, M., Lima, C. F., & Sastry, K. (2007). Analyzing Probabilistic Models in Hierarchical BOA on Traps and Spin Glasses. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2007), 523-530. [pdf]
Pelikan, M., Kalapala, R., & Hartmann, A. K. (2007). Hybrid Evolutionary Algorithms on Minimum Vertex Cover for Random Graphs. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2007), 547-554. [pdf]
Pelikan, M., & Laury, Jr., J. D. (2007). Order or Not: Does Parallelization of Model Building in hBOA Affect Its Scalability? ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2007), 555-561. [pdf]
Sastry, K., Pelikan, M. & Goldberg, D. E. (2007). Empirical Analysis of Ideal Recombination on Random Decomposable Problems. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2007), 1388-1395. [pdf]
Yu, T.-L., Sastry, K., Goldberg, D. E., & Pelikan, M. (2007). Population sizing for entropy-based model building in genetic algorithms. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2007), 601-608. [pdf]
Lima, C.F., Pelikan, M., Goldberg, D.E., Lobo, F., Sastry, K., & Hauschild, M. (2007). Influence of Selection and Replacement Strategies on Linkage Learning in BOA. IEEE International Conference on Evolutionary Computation (CEC-2007), 1083-1090. [pdf]
Butz, M. V., & Pelikan, M. (2006). Studying XCS/BOA learning in Boolean functions: Structure encoding and random boolean functions. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2006), 1449-1456. [pdf]
Lima, C. F., Pelikan, M., Sastry, K., Butz, M. V. & Goldberg, D. E. (2006). Substructural neighborhoods for local search in the Bayesian optimization algorithm. Parallel Problem Solving from Nature (PPSN IX), 232-241. [pdf]
Pelikan, M., Hartmann, A., & Sastry, K. (2006). Hierarchical BOA, cluster exact approximation, and Ising spin glasses. Parallel Problem Solving from Nature (PPSN IX), 122-131. [pdf]
Pelikan, M., Sastry, K., & Butz, M. (2006). Performance of evolutionary algorithms on random decomposable problems. Parallel Problem Solving from Nature (PPSN IX), 788-797. [pdf]
Pelikan, M., Sastry, K. & Goldberg, D. E. (2006). Sporadic model building for efficiency enhancement of hierarchical BOA. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2006), 405-412. [pdf]
Tsutsui, S., Pelikan, M., & Ghosh, A. (2005). Performance of aggregation pheromone system on unimodal and multimodal problems. IEEE Congress on Evolutionary Computation (CEC-2005), 880-887. [pdf]
Tsutsui, S., Pelikan, M., & Ghosh, A. (2005). Effect of local search on edge histogram based sampling algorithms for permutation problems. Proceedings of the Sixth Metaheuristics International Conference (MIC 2005), 865-872. [pdf]
Butz, M. V., Pelikan, M., Llora, X., Goldberg, D.E. (2005). Extracted global structure makes local building block processing effective in XCS. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2005), 655-662. [pdf]
Ondas, R., Pelikan, M., Sastry, K. (2005). Genetic Programming, Probabilistic Incremental Program Evolution, and Scalability. WSC10: 10th Online World Conference on Soft Computing in Industrial Applications, 363-372. [pdf]
Pelikan, M., Sastry, K. & Goldberg, D. E. (2005). Multiobjective hBOA, clustering, and scalability. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2005), 663-670. [pdf]
Pelikan, M. & Lin, T.-K. (2004). Parameter-less hierarchical BOA. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2004), 24-35. [pdf]
Pelikan, M., Ocenasek, J., Trebst, S., Troyer, M., & Alet, F. (2004). Computational complexity and simulation of rare events of Ising spin glasses. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2004), 36-47. [pdf]
Pelikan, M. & Sastry, K. (2004). Fitness inheritance in the Bayesian optimization algorithm. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2004), 48-59. [pdf]
Sastry, K., Pelikan, M., & Goldberg, D. E. (2004). Efficiency enhancement of genetic algorithms via building-block-wise fitness estimation. Proceedings of the IEEE International Conference on Evolutionary Computation (CEC-2004), 720-727. [pdf]
Sastry, K., Pelikan, M., & Goldberg, D. E. (2004). Limits of scalability of multiobjective estimation of distribution algorithms. Proceedings of the IEEE International Conference on Evolutionary Computation (CEC-2005), 2217-2224. [pdf]
Ocenasek, J., Schwarz, J., & Pelikan, M. (2003). Design of multithreaded estimation of distribution algorithms. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2003), 1247-1258. [pdf]
Pelikan, M., & Goldberg, D. E. (2003). Hierarchical BOA solves Ising spin glasses and MAXSAT. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2003), 1271-1282. [pdf]
Pelikan, M., Goldberg, D. E., & Tsutsui, S. (2002). Combining the strengths of the Bayesian optimization algorithm and adaptive evolution strategies. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2002), 512-519. [pdf]
Butz, M. V., & Pelikan, M. (2001). Analyzing the evolutionary pressures in XCS. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2001), 935-942. [pdf]
Pelikan, M., & Goldberg, D. E. (2001). Escaping hierarchical traps with competent genetic algorithms. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2001), 511-518. [link]
Pelikan, M., Goldberg, D. E., & Sastry, K. (2001). Bayesian optimization algorithm, decision graphs, and Occam's razor. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2001), 519-526. [pdf]
Sastry, K., Goldberg, D. E., & Pelikan, M. (2001). Don't evaluate, inherit. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2001), 551-558. [pdf]
Tsutsui, S., Pelikan, M. & Goldberg, D. E. (2001). Evolutionary algorithm using marginal histogram models in continuous domain. Knowledge-Based Intelligent Information Engineering Systems & Allied Thechnologies (KES-2001), 112-121. [pdf]
Lobo, F. G., Goldberg, D. E., & Pelikan, M. (2000). Time complexity of genetic algorithms on exponentially scaled problems. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2000), 151-158. [pdf]
Pelikan, M., & Goldberg, D. E. (2000a). Genetic algorithms, clustering, and the breaking of symmetry. Parallel Problem Solving from Nature, 385-394. [pdf]
Pelikan, M., & Goldberg, D. E. (2000b). Hierarchical problem solving and the Bayesian optimization algorithm. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2000), 275-282. [pdf]
Pelikan, M., Goldberg, D. E., & Cantu-Paz, E. (2000a). Bayesian optimization algorithm, population sizing, and time to convergence. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2000), 275-282. [pdf]
Pelikan, M., Goldberg, D.E., & Lobo, F. (2000). A survey to optimization by building and using probabilistic models. Proceedings of the American Control Conference 2000 (ACC-2000), 3289-3293.
Pelikan, M. (1999). Preserving the linkage by the BOA. Proceedings of the International Conference on Genetic Algorithms (Mendel 99).
Pelikan, M., Goldberg, D. E., & Cantu-Paz, E. (1999). BOA: The Bayesian optimization algorithm. ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-99), I , 525-532. [pdf]
Pelikan, M., & Mu ̈hlenbein, H. (1999). The bivariate marginal distribution algorithm. Advances in Soft Computing Engineering Design and Manufacturing, 521-535. [pdf]
Pelikan, M., & Muhlenbein, H. (1998). Marginal distributions in evolutionary algorithms. Proceedings of the International Conference on Genetic Algorithms Mendel '98, 90-95.
Kvasnicka, V., Pospichal, J., & Pelikan, M. (1996a). Read's linear codes and evolutionary computation over population of rooted trees. In Intelligent Technologies '96, Volume II (pp. 141-154). Slovakia.
Kvasnicka, V., Pospichal, J., & Pelikan, M. (1996b). Stochastic simulation of multiagent models. In Intelligent Technologies '96, Volume II (pp. 165-184). Slovakia.

Books

Keijzer, M., Antoniol, G., Bates Congdon, C., Deb, K., Doerr, B., Hansen, N., Holmes, J.H., Hornby, G.S., Howard, D., Kennedy, J., Kumar, S., Lobo, F.G., Miller, J.F., Moore, J., Neumann, F., Pelikan, M., Pollack, J., Sastry, K., Stanley, K., Stoica, A., Talbi, E.-G., Wegender, I. (2008). Proceedings of the ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2008), ACM Press.
Thierens, D., Beyer, H.-G., Birattari, M., Bongard, J., Branke, J., Clark, J. A., Cliff, D., Congdon, C. B., Deb, K., Doerr, B., Kovacs, T., Kumar, S., Miller, J. F., Moore, J., Neumann, F., Pelikan, M., Poli, R., Sastry, K., Stanley, K. O., Stuetzle, T., Watson, R. A., Wegener, I., eds. (2007). Proceedings of the ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2007), ACM Press.
Pelikan, M., Sastry, K. & Cantu-Paz, E., eds. (2006). Scalable optimization via probabilistic modeling: From algorithms to applications. Springer-Verlag. [link]
Beyer, H.-G., O'Reilly, U. M., Arnold, D. V., Banzhaf, W., Blum, C., Bonabeau, E. W., Cantu-Paz, E., Dasgupta, D., Deb, K., Foster, J. A., de Jong, E. D., Lipson, H., Llora, X., Mancoridis, S., Pelikan, M., Raidl, G. R., Soule, T., Tyrrell, A. M., Watson, J.-P., Zitzler, E., eds. (2005). Proceedings of the ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2005), ACM Press.
Pelikan, M. (2005). Hierarchical Bayesian optimization algorithm: Toward a new generation of evolutionary algorithms. Springer-Verlag. [link]

Refereed Journal Papers

Helmi, B.H., Rahmani, A.T., and Pelikan, M. (2014). A factor graph based genetic algorithm. International Journal of Applied Mathematics and Computer Science, 24 (9), 621-633. [pdf]
Hauschild, M., Pelikan, M., Sastry, K., Goldberg, D.E. (2012). Using previous models to bias structural learning in the hierarchical BOA. Evolutionary Computation, 20 (1), 135-160. [pdf]
Pelikan, M., Hauschild, M. (2011). An introduction and survey of estimation of distribution algorithms. Swarm and Evolutionary Computation, 1 (3), 111-128. [pdf]
Lima, C. F., Lobo, F. G., Pelikan, M., Goldberg, D.E. (2011). Model accuracy in the Bayesian optimization algorithm. Soft Computing, 15 (7), 1351-1371. [pdf]
Hammel, M., Yu, Y., Mahaney, B. L., Cai, B., Ye, R., Phipps, B. M., Rambo, R. P., Hura, G. L., Pelikan, M., So, S., Abolfath, R. M., Chen, D. J., Lees-Miller, S. P., and Tainer, J. A. (2010). Ku and DNA-dependent protein kinase (DNA-PK) dynamic conformations and assembly regulate DNA binding and the initial nonhomologous end joining complex. The Journal of Biological Chemistry, 285, 1414-1423. [pdf]
Csefalvayova, L, Pelikan, M, Kralj Cigic, I, Kolar, J, Strlic, M (2010). Use of genetic algorithms with multivariate regression for determination of gelatine in historic papers based on FT-IR and NIR spectral data. Talanta, 82 (5), 1784-1790. [pdf]
Hauschild, M., Pelikan, M., Lima, C.F., Sastry, K. (2009). Analyzing Probabilistic Models in Hierarchical BOA on Traps and Spin Glasses. IEEE Transactions on Evolutionary Computation, 13 (6), 1199-1217. [link]
Pelikan, M., Hura, G.L., Hammel, M. (2009). Structure and Flexibility within Proteins as Identified through Small Angle X-ray Scattering. General Physiology and Biophysics, 28 (2), 174-189. [pdf]
Yu, T.-L., Goldberg, D.E., Sastry, K., Lima, C.F., Pelikan, M. (2009). Dependency Structure Matrix, Genetic Algorithms, and Effective Recombination. Evolutionary Computation, 17 (4), 595-626. [pdf]
Bernstein, N.K., Hammel, M., Mani, R.S., Weinfeld, M., Pelikan, M., Tainer, J.A., and Glover, J.N.M. (2009). Mechanism of DNA substrate recognition by the mammalian DNA repair enzyme, Polynucleotide Kinase. Nucleic Acids Research, 37 (18), 6161-6173. [html]
Pelikan, M., Sastry, K., Goldberg, D.E. (2008). Sporadic Model Building for Efficiency Enhancement of Hierarchical BOA. Genetic Programming and Evolvable Machines, 9 (1), 53-84. [pdf]
Tsutsui, S., Pelikan, M., & Ghosh, A. (2006). Edge Histogram Based Sampling with Local Search for Solving Permutation Problems. International Journal of Hybrid Intelligent Systems, 3 (1), 11-22. [pdf]
Butz, M. V., Pelikan, M., Llora, X., & Goldberg, D. E. (2006). Automated global structure extraction for effective local building block processing in XCS. Evolutionary Computation, 14 (3), 345-380. [pdf]
Potthast, F., Ocenasek, J., Rutishauser, D., Pelikan, M., & Schlapbach, R. (2005). Database independent detection of isotopically labeled MS/MS spectrum peptide pairs. Journal of Chromatography B, 817(2), 225-230. [link]
Pelikan, M., & Goldberg, D. E. (2003). A hierarchy machine: Learning to optimize from nature and humans. Complexity, 8(5), 36-45. [link]
Pelikan, M., Goldberg, D. E., & Tsutsui, S. (2003). Getting the best of both worlds: Discrete and continuous genetic and evolutionary algorithms in concert. Information Sciences, 156(3-4), 147-171. [pdf]
Pelikan, M., Goldberg, D. E., & Lobo, F. (2002). A survey of optimization by building and using probabilistic models. Computational Optimization and Applications, 21(1), 5-20. [pdf]
Pelikan, M., Sastry, K., & Goldberg, D. E. (2002). Scalability of the Bayesian optimization algorithm. International Journal of Approximate Reasoning, 31(3), 221-258. [pdf]
Tsutsui, S., Pelikan, M., & Goldberg, D. E. (2002). Probabilistic model-building genetic algorithms using histogram models in continuous domain. Journal of the Information Processing Society of Japan, 43.
Pelikan, M., Goldberg, D. E., & Cantu-Paz, E. (2000b). Linkage problem, distribution estimation, and Bayesian networks. Evolutionary Computation, 8(3), 311-341. [pdf]
Kvasnicka, V., Pelikan, M., & Pospichal, J. (1996). Hill climbing with learning (An abstraction of genetic algorithm). Neural Network World, 6, 773-796.

Book Chapters and Encyclopedia Articles

Pelikan, M., Hauschild, M.W., Lobo, F.G. (2014). Introduction to estimation of distribution algorithms. In Handbook of Computational Intelligence, Springer. [link]
Pelikan, M. (2011). Genetic algorithms. In Wiley Encyclopedia of Operations Research and Management Science, James J. Cochran (Ed.), Wiley. [link]
Pelikan, M. (2010). Evolucne algoritmy. In Umela Inteligencia a Kognitivna Veda I, V. Kvasnicka et al. (Eds.), 335-353, Slovak Technical University Press. In Slovak.
Lima, C.F., Pelikan, M., Goldberg, D.E., Lobo, F.G., Sastry, K., and Hauschild, M. (2008). Linkage Learning Accuracy in the Bayesian Optimization Algorithm. In Linkage in Evolutionary Computation, Y.-P. Chen et al. (Eds.), 87-107, Springer. [link]
Pelikan, M., Hartmann, A.K., & Lin, T.-K. (2007). Parameter-less Hierarchical Bayesian Optimization Algorithm. In Parameter Setting in Evolutionary Algorithms, Lobo, Lima, & Michalewicz (eds.), Springer.
Ocenasek, J., Cantu-Paz, E., Pelikan, M., & Schwarz, J. (2006). Design of Parallel Estimation of Distribution Algorithms. In Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications, Pelikan, Sastry, & Cantu-Paz (eds.), Springer.
Pelikan, M., Sastry, K., & Cantu-Paz, E. (2006). Introduction. In Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications, Pelikan, Sastry, & Cantu-Paz (eds.), Springer.
Pelikan, M., & Goldberg, D.E. (2006). Hierarchical Bayesian Optimization Algorithm. In Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications, Pelikan, Sastry, & Cantu-Paz (eds.), Springer.
Pelikan, M., Sastry, K., & Goldberg, D.E. (2006). Multiobjective Estimation of Distribution Algorithms. In Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications, Pelikan, M., Sastry, K., & Cantu-Paz, E. (eds.), Springer.
Pelikan, M., & Hartmann, A. (2006). Searching for Ground States of Ising Spin Glasses with Hierarchical BOA and Cluster Exact Approximation. In Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications, Pelikan, Sastry, & Cantu-Paz (eds.), Springer.
Sastry, K., Pelikan, M., & Goldberg, D. E. (2006). Efficiency Enhancement of Estimation of Distribution Algorithms. In Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications, Pelikan, Sastry, & Cantu-Paz (eds.), Springer.
Butz, M., Pelikan, M., Llora, X., & Goldberg, D.E. (2006). Effective and Reliable Online Classification Combining XCS with EDA Mechanisms. In Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications, Pelikan, Sastry, & Cantu-Paz (eds.), 249-274, Springer.