World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
11256
World Ranking
10472
National Ranking
4379

Overview

Erick Cantú-Paz is affiliated with Amazon in the United States, where they engage in research activities. Their career is associated with this organization based in the U.S.

Although detailed information about their recent papers, co-authors, publication venues, book publications, and specific fields or subfields of study is not available, the profile reflects a researcher actively involved in an environment known for technological development and innovation.

No records of awards or notable distinctions have been documented for Erick Cantú-Paz. The absence of listed recent publications or collaborations suggests either a focus on non-published research, proprietary work, or emerging projects that may not yet be publicly disclosed.

The profile indicates a professional whose expertise is connected to Amazon, a major technology and research-driven company, implying involvement in applied or theoretical research areas aligning with the organization's industry sectors.

Best Publications

  • A Survey of Parallel Genetic Algorithms

    Erick Cantú-Paz

  • BOA: the Bayesian optimization algorithm

    Martin Pelikan;David E. Goldberg;Erick Cantú-Paz

  • Efficient and Accurate Parallel Genetic Algorithms

    Erick Cantu-Paz

  • The gambler's ruin problem, genetic algorithms, and the sizing of populations

    George Harik;Erick Cantú-Paz;David E. Goldberg;Brad L. Miller

  • Genetic and Evolutionary Computation -- GECCO-2003

    Erick Cantú-Paz;James A. Foster;Kalyanmoy Deb;Lawrence David Davis

  • Linkage Problem, Distribution Estimation, and Bayesian Networks

    Martin Pelikan;David E. Goldberg;Erick E. Cantú-paz

  • Migration Policies, Selection Pressure, and Parallel Evolutionary Algorithms

    Erick Cantú-Paz

  • Efficient parallel genetic algorithms: theory and practice

    Erick Cantú-Paz;David E. Goldberg

  • Scalable Optimization via Probabilistic Modeling

    Martin Pelikan;Kumara Sastry;Erick Cantu-Paz

  • Scalable optimization via probabilistic modeling : from algorithms to applications

    Martin Pelikan;Kumara Sastry;Erick Cantú-Paz

  • Inducing oblique decision trees with evolutionary algorithms

    E. Cantu-Paz;C. Kamath

  • An empirical comparison of combinations of evolutionary algorithms and neural networks for classification problems

    E. Cantu-Paz;C. Kamath

  • Proceedings of the Genetic and Evolutionary Computation Conference

    William B. Langdon;Erick Cantú-Paz;Keith E. Mathias;Rajkumar Roy

  • Personalized click prediction in sponsored search

    Haibin Cheng;Erick Cantú-Paz

  • Topologies, migration rates, and multi-population parallel genetic algorithms

    Erick Cantú-Paz

  • Bayesian optimization algorithm, population sizing, and time to convergence

    Martin Pelikan;David E. Goldberg;Erick Cantu-Paz

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

    Martin Pelikan;Kumara Sastry;Erick Cantú-Paz

  • The 2003 Genetic and Evolutionary Computation Conference

    James A. Foster;Erick Cantu-Paz

  • Parallel object-oriented data mining system

    Chandrika Kamath;Erick Cantu-Paz

  • Feature selection in scientific applications

    Erick Cantú-Paz;Shawn Newsam;Chandrika Kamath

  • Designing Efficient and Accurate Parallel Genetic Algorithms

    Erick Cantu-Paz

Frequent Co-Authors

David E. Goldberg
David E. Goldberg University of Illinois at Urbana-Champaign
Martin Pelikan
Martin Pelikan University of Missouri
Alan C. Schultz
Alan C. Schultz United States Naval Research Laboratory
Julian F. Miller
Julian F. Miller University of York
Rajkumar Roy
Rajkumar Roy City, University of London
Stewart W. Wilson
Stewart W. Wilson University of Illinois at Urbana-Champaign
William B. Langdon
William B. Langdon University College London
Vasant Honavar
Vasant Honavar Pennsylvania State University
Riccardo Poli
Riccardo Poli University of Essex
Edmund K. Burke
Edmund K. Burke Bangor University

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