D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 33 Citations 9,859 77 World Ranking 8321 National Ranking 3856

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Algorithm
  • Machine learning

His scientific interests lie mostly in Mathematical optimization, Algorithm, Evolutionary computation, Evolutionary algorithm and Genetic algorithm. His studies deal with areas such as Quality, Noise and Selection as well as Mathematical optimization. His work on Parallel algorithm is typically connected to Network topology, Sizing and Random walk as part of general Algorithm study, connecting several disciplines of science.

Erick Cantú-Paz combines subjects such as Backpropagation, Feature, Theoretical computer science and Pattern recognition with his study of Evolutionary computation. His Genetic algorithm research is multidisciplinary, relying on both Estimation of distribution algorithm and Multivariate statistics. His work investigates the relationship between Estimation of distribution algorithm and topics such as Bayesian network that intersect with problems in Time complexity.

His most cited work include:

  • BOA: the Bayesian optimization algorithm (813 citations)
  • A Survey of Parallel Genetic Algorithms (813 citations)
  • Efficient and Accurate Parallel Genetic Algorithms (723 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Mathematical optimization, Artificial intelligence, Genetic algorithm, Algorithm and Evolutionary computation. His work in Mathematical optimization addresses subjects such as Selection, which are connected to disciplines such as Feature. His Artificial intelligence research integrates issues from Machine learning, Data mining and Pattern recognition.

His work is dedicated to discovering how Genetic algorithm, Estimation of distribution algorithm are connected with Probabilistic logic and other disciplines. His research ties Markov chain and Algorithm together. His Evolutionary computation research focuses on subjects like Theoretical computer science, which are linked to Genetic representation.

He most often published in these fields:

  • Mathematical optimization (33.75%)
  • Artificial intelligence (27.50%)
  • Genetic algorithm (21.25%)

What were the highlights of his more recent work (between 2006-2016)?

  • Data mining (16.25%)
  • Information retrieval (7.50%)
  • Ranking (5.00%)

In recent papers he was focusing on the following fields of study:

Erick Cantú-Paz spends much of his time researching Data mining, Information retrieval, Ranking, Search engine and User feedback. His study in Data mining intersects with areas of studies such as Set and Distribution. The various areas that Erick Cantú-Paz examines in his Information retrieval study include Quality and Task, Artificial intelligence.

In his papers, he integrates diverse fields, such as Ranking and Revenue. Erick Cantú-Paz has included themes like Machine learning and Relevance in his Search engine study. His study in Relevance is interdisciplinary in nature, drawing from both Web search query, Aggregate and Pattern recognition.

Between 2006 and 2016, his most popular works were:

  • Personalized click prediction in sponsored search (115 citations)
  • Temporal click model for sponsored search (44 citations)
  • Dynamic layout for a search engine results page based on implicit user feedback (40 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Algorithm

Erick Cantú-Paz mainly focuses on Information retrieval, Search engine, Search engine results page, World Wide Web and User feedback. His Information retrieval research spans across into subjects like Focus and User experience design. There are a combination of areas like Machine learning, Artificial intelligence, Sequence, Click model and Click-through rate integrated together with his Focus study.

He frequently studies issues relating to Quality and Machine learning. He undertakes multidisciplinary investigations into Search engine results page and Dynamic search in his work. His biological study spans a wide range of topics, including Ranking and Data mining.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

A Survey of Parallel Genetic Algorithms

Erick Cantú-Paz.
(2000)

1512 Citations

BOA: the Bayesian optimization algorithm

Martin Pelikan;David E. Goldberg;Erick Cantú-Paz.
genetic and evolutionary computation conference (1999)

1359 Citations

Efficient and Accurate Parallel Genetic Algorithms

Erick Cantu-Paz.
(2000)

1311 Citations

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

George Harik;Erick Cantú-Paz;David E. Goldberg;Brad L. Miller.
Evolutionary Computation (1999)

845 Citations

Genetic and Evolutionary Computation -- GECCO-2003

Erick Cantú-Paz;James A. Foster;Kalyanmoy Deb;Lawrence David Davis.
(2003)

579 Citations

Linkage Problem, Distribution Estimation, and Bayesian Networks

Martin Pelikan;David E. Goldberg;Erick E. Cantú-paz.
Evolutionary Computation (2000)

439 Citations

Migration Policies, Selection Pressure, and Parallel Evolutionary Algorithms

Erick Cantú-Paz.
Journal of Heuristics (2001)

265 Citations

Efficient parallel genetic algorithms: theory and practice

Erick Cantú-Paz;David E. Goldberg.
Computer Methods in Applied Mechanics and Engineering (2000)

249 Citations

Scalable Optimization via Probabilistic Modeling

Martin Pelikan;Kumara Sastry;Erick Cantu-Paz.
(2006)

240 Citations

Scalable optimization via probabilistic modeling : from algorithms to applications

Martin Pelikan;Kumara Sastry;Erick Cantú-Paz.
(2006)

236 Citations

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