The most updated list of my publications is in my vita (in pdf). Let me know if you want a paper that is not downloadable from below.

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Books

Cantú-Paz, E. (2000). Efficient and Accurate Parallel Genetic Algorithms. Boston, MA: Kluwer Academic Publishers. ISBN 0-7923-7221-2. More info. Buy

E. Cantú-Paz, Foster, J.A., Deb, K., Davis, D., Roy, R., O'Reilly, U.-M., Kendall, G., Standish, R., Beyer, H.-G., Wilson, S., Harman, M., Wegener, J., Dasgupta, D., Schultz, A.C., Potter, M.A., Jonoska, N., Dowsland, K.A., Miller, J. (Editors). Genetic and Evolutionary Computation -- GECCO-2003. Berlin: Springer Verlag, 2003.

Langdon, W. B., Cantú-Paz, E., Mathias, K., Roy, R., Davis, D., Poli, R., Balakrishnan, K., Honavar, V., Rudolph, G., Wegener, J., Bull, L., Potter, M.A., Schultz, A.C., Miller, J.F., Burke, E., Jonoska, N. (Eds.) (2002). GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference. San Mateo, CA: ISBN 1-55860-878-8. Buy book or CD-ROM

Whitley, D., Goldberg, D.E., Cantú-Paz, E., Spector, L., Parmee, I., and Beyer, H.-G. (Eds.) (2000). GECCO 2000: Proceedings of the Genetic and Evolutionary Computation Conference. San Mateo, CA: Morgan Kaufmann.ISBN 1-55860-708-0. Buy

Cantú-Paz, E. (1999). Designing Efficient and Accurate Parallel Genetic Algorithms. PhD thesis. University of Illinois at Urbana-Champaign.  Abstract

Kamath, C., Cantú-Paz, E., Littau, D. Using histograms to introduce randomization in the generation of ensembles of decision trees. US Patent 6,859,804. Issued 2-22-2005.

Kamath, C., Cantú-Paz, E. Parallel object-oriented data mining system. US Patent 6,675,164. Issued 01-06-2004.

Cantú-Paz, E., Kamath, C. Creating ensembles of oblique decision trees with evolutionary algorithms and sampling. Patent Application.

Kamath, C., Cantú-Paz, E. Generating ensembles of decision trees by sampling data instances at each node of the tree. Patent Application.

Kamath, C., Cantú-Paz, E. Parallel object-oriented decision tree system. Patent Application.

Cantú-Paz, E. and Kamath, C. (in press). An empirical comparison of combinations of evolutionary algorithms and neural networks for classification problems. IEEE Transactions on System, Man, and Cybernetics, Part B.

Cantú-Paz, E. and Kamath, C. (2003). Evolving neural networks to identify bent-double galaxies in the FIRST survey. Neural Networks. 16 (3-4), 507-517. pdf

Cantú-Paz, E and Kamath, C. (2003). Inducing oblique decision trees with evolutionary algorithms. IEEE Transactions on Evolutionary Computation. 7(1), 54-68. pdf

Kamath, C., Cantú-Paz, E., Fodor, I.K. and N. Tang (2002). Classifying bent-double galaxies. IEEE Computing in Science and Engineering. 4(4), 52-60. pdf

Cantú-Paz, E. (2002). Order statistics and selection methods of evolutionary algorithms. Information Processing Letters. 82(1), 15-22. ps.gz

Cantú-Paz, E.  (2001). Migration policies, selection pressure, and parallel evolutionary algorithms. Journal of Heuristics. 7(4), 311-334. ps.gz pdf

Pelikan, M., Goldberg, D.E., and Cantú-Paz, E. (2000). Linkage problem, distribution estimation, and Bayesian networks. Evolutionary Computation. 8(3), 311-340. pdf

Cantú-Paz, E.  (2000). Markov chain models of parallel genetic algorithms. IEEE Transactions on Evolutionary Computation.4(3), 216-226. pdf

Cantú-Paz, E. and Goldberg, D.E. (2000). Efficient parallel genetic algorithms: theory and practice. Computer Methods in Applied Mechanics and Engineering. 186, 221-238. ps.gz

Cantú-Paz, E. and Goldberg, D.E. (1999). On the scalability of parallel genetic algorithms. Evolutionary Computation. 7(4), 429-449. pdf

Harik, G., Cantú-Paz, E., Goldberg, D.E., and Miller, B. (1999). The gambler's ruin  problem, genetic algorithms, and the sizing of populations.Evolutionary Computation. 7(3) (Extended version of Harik et al, 1997) pdf

Cantú-Paz, E. (1998). A survey of parallel genetic algorithms. Calculateurs Paralleles, Reseaux et Systems Repartis. Vol. 10, No. 2. pp. 141-171. Paris: Hermes. ps.gz Abstract

Cantú-Paz, E., Newsam, S., and Kamath, C. (2004). Feature selection for scientific applications In Proceedings of the SIGKDD International Conference on Knowledge Discovery and Data Mining. pdf

Fernández, F., Cantú-Paz, E., López, J.I., and T. Manzano. (2004). Saving resources with plagues in genetic algorithms In Parallel Problem Solving from Nature. pdf

Cantú-Paz, E. (2004). Feature subset selection, class separability, and genetic algorithms In Deb, K. et al (Eds.) Genetic and Evolutionary Computation Conference -- GECCO-2004. Berlin: Springer Verlag. One of five nominees for best paper award out of 158 submissions to the GA track. pdf

Cantú-Paz, E. (2004). Adaptive sampling for noisy problems In Deb, K. et al (Eds.) Genetic and Evolutionary Computation Conference -- GECCO-2004. Berlin: Springer Verlag. pdf

Cantú-Paz, E. and Goldberg, D. E. (2003). Are multiple runs of genetic algorithms better than one? In Cantú-Paz, E. et al. (Eds.). Genetic and Evolutionary Computation Conference -- GECCO-2003. (pp. 801--812). Berlin: Springer Verlag. One of five nominees for best paper award out of 160 submissions to the GA track. pdf

Cantú-Paz, E. (2003). Pruning Neural Networks with Distribution Estimation Algorithms. In Cantú-Paz, E. et al. (Eds.). Genetic and Evolutionary Computation Conference -- GECCO-2003. (pp. 790--800). Berlin: Springer Verlag. pdf

Cantú-Paz, E. and Kamath, C. (2002). Evolving neural networks for the classification of galaxies. In W. B. Langdon, E. Cantu-Paz, K. Mathias, R. Roy, D. Davis, R. Poli, K. Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull, M. A. Potter, A. C. Schultz, J. F. Miller, E. Burke, N. Jonoska (Eds.), GECCO-2002: Proceedings of the Genetic and Evolutionary Computation Conference.  (pp. 754).  San Francisco, CA: Morgan Kaufmann. Winner (tied) of best-paper award for the real-world applications track. pdf

Cantú-Paz, E. (2002). On random numbers and the performance of genetic algorithms. In W. B. Langdon, E. Cantu-Paz, K. Mathias, R. Roy, D. Davis, R. Poli, K. Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull, M. A. Potter, A. C. Schultz, J. F. Miller, E. Burke, N. Jonoska (Eds.), GECCO-2002: Proceedings of the Genetic and Evolutionary Computation Conference.  (pp. 754).  San Francisco, CA: Morgan Kaufmann. pdf

Cantú-Paz, E. (2002). Feature subset selection by estimation of distribution algorithms. In W. B. Langdon, E. Cantu-Paz, K. Mathias, R. Roy, D. Davis, R. Poli, K. Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull, M. A. Potter, A. C. Schultz, J. F. Miller, E. Burke, N. Jonoska (Eds.), GECCO-2002: Proceedings of the Genetic and Evolutionary Computation Conference.  (pp. 754).  San Francisco, CA: Morgan Kaufmann. pdf

Kamath, C., Cantú-Paz, E. and Littau, D. (2002). Approximate splitting for ensembles of trees using histograms. In Second SIAM International Conference on Data Mining (SDM-2002). pdf

Kirshner, S., Cadez, I. V., Smyth, P., Kamath C., and Cantu-Paz, E., (2002) Probabilistic model-based detection of bent-double radio galaxies. In Proceedings of the International Conference on Pattern Recognition, ICPR 2002 pdf

Cantú-Paz, E. (2001). Single vs. multiple runs under constant computation cost. In Spector, L., Goodman, E., Wu, A., Langdon, W.B., Voigt, H.-M., Gen, M., Sen, S., Dorigo, M., Pezeshk, S., Garzon, M., Burke, E. (Eds.), GECCO-2001: Proceedings of the Genetic and Evolutionary Computation Conference.  (pp. 754).  San Francisco, CA: Morgan Kaufmann. pdf

Cantú-Paz, E. (2000). Selection intensity in genetic algorithms with generation gaps. In Whitley, D., Goldberg, D.E., Cantú-Paz, E.,  Spector, L., Parmee, I. and Beyer, H.-G. (Eds.), GECCO-2000: Proceedings of the Genetic and Evolutionary Computation Conference.  (pp. 911-918).  San Francisco, CA: Morgan Kaufmann.ps.gz

Cantú-Paz, E., Kamath, C. (2000). Using evolutionary algorithms to induce oblique decision trees. In Whitley, D., Goldberg, D.E., Cantú-Paz, E.,  Spector, L., Parmee, I. and Beyer, H.-G. (Eds.), GECCO-2000:  Proceedings of the Genetic and Evolutionary Computation Conference.  (pp. 1053-1060). San Francisco, CA: Morgan Kaufmann. ps.gz pdf

Pelikan, M., Goldberg, D.E. & Cantú-Paz, E. (2000). Bayesian Optimization Algorithm, population size, and time to convergence. In Whitley, D., Goldberg, D.E., Cantú-Paz, E.,  Spector, L., Parmee, I. and Beyer, H.-G. (Eds.), GECCO-2000: Proceedings of the Genetic and Evolutionary Computation Conference.  (pp. 275-282).  San Francisco, CA: Morgan Kaufmann.ps.gz

Cantú-Paz, E. (1999). Migration policies and takeover times in parallel genetic algorithms.  In Banzhaf, W., Daida, J., Eiben, A. E., Garzon, M. H., Honavar, V., Jakiela, M., and Smith, R. E. (Eds.) GECCO-99: Proceedings of the Genetic and Evolutionary Computation Conference. (p. 775). San Francisco, CA: Morgan Kaufmann. ps.gz

Cantú-Paz, E. (1999). Topologies, migration rates, and multi-population parallel genetic algorithms.   In Banzhaf, W., Daida, J., Eiben, A. E., Garzon, M. H., Honavar, V., Jakiela, M., and Smith, R. E. (Eds.) GECCO-99: Proceedings of the Genetic and Evolutionary Computation Conference. (pp. 91-98). San Francisco, CA: Morgan Kaufmann. ps.gz

Pelikan, M. Goldberg, D.E., and Cantú-Paz, E. (1999). BOA: The Bayesian optimization algorithm. In Banzhaf, W., Daida, J., Eiben, A. E., Garzon, M. H., Honavar, V., Jakiela, M., and Smith, R. E. (Eds.) GECCO-99: Proceedings of the Genetic and Evolutionary Computation Conference. (pp. 525-532). San Francisco, CA: Morgan Kaufmann. ps.gz

Cantú-Paz, E. (1998).  Using Markov chains to analyze a bounding case of  parallel genetic algorithms.  In Koza, J., Banzhaf, W., Chellapilla, K., Deb, K., Dorigo, M., Fogel, D., Garzon, M., Goldberg, D. E., Iba, H. & Riolo, R. (Eds.), Genetic Programming: Proceedings of the Third Annual Conference. (pp.  456-462).  San Francisco, CA: Morgan Kaufmann. ps.Z

Cantú-Paz, E.,  Designing efficient master-slave parallel genetic algorithms. In Koza, J., Banzhaf, W., Chellapilla, K., Deb, K., Dorigo, M., Fogel, D., Garzon, M., Goldberg, D. E., Iba, H. & Riolo, R. (Eds.), Genetic Programming: Proceedings of the Third Annual Conference. (pp. 455). San Francisco, CA: Morgan Kaufmann. ps.Z

Harik, G., Cantú-Paz, E., Goldberg, D. E., and Miller, B. (1997). The gambler's ruin problem, genetic algorithms, and the sizing of populations In Back, T. (Ed.) Proceedings of the IEEE International Conference on Evolutionary Computation. (pp 7-12). New York, NY: IEEE Press. ps.Z

Cantú-Paz, E., and Goldberg, D.E., (1997). Modeling idealized bounding cases of parallel genetic algorithms. In Koza, J., Deb, K., Dorigo, M., Fogel, D., Garzon, M., Iba, H., & Riolo, R. (Eds.), Genetic Programming: Proceedings of the Second Annual Conference. (pp. 353-361).  San Francisco, CA: Morgan Kaufmann. [ps.Z 

Cantú-Paz, E., and Goldberg D.E. (1997). Predicting speedups of idealized bounding cases of parallel genetic algorithms. In Back, T. (Ed.) Proceedings of the Seventh International Conference on Genetic Algorithms. San Mateo, CA: Morgan Kaufmann. ps.Z

Cantu-Paz, E. and Kamath, C. (2002). On the use of evolutionary algorithms in data mining. In Abbass, H., Sarker, R., and Newton, C. (Eds.) Data Mining: a Heuristic Approach. pp. 48-71. Hershey, PA: IDEA Group Publishing. pdf

Kamath, C., Cantu-Paz, E., Fodor, I., and Tang, N. (2001). Searching for bent-double galaxies in the FIRST survey. In Grossman, R., Kamath, C., Kegelmeyer, W., Kumar, V., Namburu, R. (Eds.) Data Mining for Scientific and Engineering Applications. pp. 95-114. Boston, MA: Kluwer.

Cantu-Paz, E. (2001). Genetic Algorithms. Encyclopedia of Computers and Computer History. Chicago, IL: Fitzroy Dearborn.

Cantu-Paz, E. (1999). Implementing fast and reliable parallel genetic algorithms. In Chalmers, L. (Ed.), Handbook of Practical Genetic Algorithms. Volume III. CRC Press. ps.gz (this is the full version of the paper with all the figures)

Cantu-Paz, E., (2001) Supervised and Unsupervised Discretization methods for Evolutionary Algorithms, Proceedings GECCO 2001 workshop on Optimization by Building and Using Probabilisitic Models. pdf

Kamath, C., E. Cantu-Paz, I. K. Fodor, N. Tang. (2001). Using data mining to find bent-double galaxies in the FIRST survey, Proceedings, Astronomical Data Analysis, at the SPIE Annual Meeting, San Diego, July-August 2001. pdf

Kamath, C., Cantu-Paz, E. (2001). Creating ensembles of decision trees through sampling. Interface: Computer Science and Statistics. Volume 34. pdf

Cantu-Paz, E. and Kamath, C. (2000). Combining evolutionary algorithms with oblique decision trees to detect bent double galaxies. In Proceedings of SPIE. Vol 4120. (pp. 63--71). San Diego, CA. ps.gz

Cantu-Paz, E. (2000). On the effects of migration on the fitness distribution of parallel evolutionary algorithms. In Workshop on Evolutionary Computation and Parallel Processing at GECCO-2000. (pp. 3--6). Las Vegas, NV ps.gz

Kamath, C., Cantu-Paz, E. (2000) On the design of a parallel object-oriented data mining toolkit. In Workshop on Distributed and Parallel Knowledge Discovery at KDD-2000. Boston, MA. ps.gz

Fodor, I., Cantu-Paz, E., Kamath, C., and Tang, N. (2000). Finding Bent-Double Radio Galaxies: A Case Study in Data Mining. Interface: Computer Science and Statistics. Volume 33. New Orleans, LA. ps.gz

Cant\'u-Paz, E. (1999). Migration policies, selection pressure, and parallel evolutionary algorithms. In Brave, S., Wu, A. (Eds.) Late Breaking Papers at the Genetic and Evolutionary Computation Conference. Orlando, FL. ps.gz

 

Cantu-Paz, E. Migration policies, selection pressure, and parallel evolutionary algorithms. IlliGAL 99015 ps.Z Abstract

Cantú-Paz, E. Migration policies and takeover times in parallel genetic algorithms. IlliGAL 99008. ps.Z Abstract

Cantú-Paz, E. Topologies, migration rates, and multi-population parallel genetic algorithms. IlliGAL 99007. ps.Z Abstract

Cantú-Paz, E. and David E. Goldberg Parallel genetic algorithms with distributed panmictic populations. IlliGAL 99006. ps.Z Abstract

Pelikan, M., Goldberg, D.E., and Cantú-Paz, E. (1999). BOA: The Bayesian optimization algorithm. IlliGAL 99003. ps.Z

Pelikan, M., Goldberg, D.E., and Cantú-Paz, E. (1999). Linkage problem, distribution estimation, and Bayesian networks. IlliGAL 98013. ps.Z

Cantú-Paz, E. A Markov chain analysis of parallel genetic algorithms with arbitrary topologies and migration rates. IlliGAL 98010. ps.Z Abstract

Cantú-Paz, E. Designing scalable multi-population parallel genetic algorithms. IlliGAL 98009. ps.Z Abstract

Cantú-Paz, E. Designing efficient master-slave parallel genetic algorithms. IlliGAL 97004. (A summarized published version is available above) ps.ZAbstract

Cantú-Paz, E. A survey of parallel genetic algorithms. IlliGAL 97003. (Revised version of IlliGAL 95007. A published version is available above) ps.ZAbstract

Goldberg, D. E., Zakrewski, K., Chang, C., Gallego, P., Sutton, B., Miller, B., Cantú-Paz, E. Genetic Algorithms: A Bibliography. IlliGAL 97002. ps.Z

Harik, G., Cantú-Paz, E., Goldberg, D. E., and Miller, B.,The Gambler's Ruin Problem, Genetic Algorithms, and the Sizing of Populations. IlliGAL 96004. (A shorter version was published in ICEC97.) ps.ZAbstract

Cantú-Paz, E. and Goldberg. D. E., Modeling Idealized Bounding Cases of Parallel Genetic Algorithms.  IlliGAL 96007. (Published version is available above) ps.ZAbstract

Cantú-Paz, E. and Goldberg, D. E., Predicting Speedups of Idealized Bounding Cases of Parallel Genetic Algorithms. IlliGAL 96008. (Published version is available above) ps.ZAbstract

Cantú-Paz, E. A summary of research on parallel genetic algorithms. IlliGAL 95007. (An updated version is available as 97003, and a second updated published version is available above) ps.Z