Genetic Programming Bibliography entries for Pablo Moscato

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GP coauthors/coeditors: Carlos Cotta, Natalie Jane de Vries, Jamie Carlson, Rodrigo Reis, Lukasz P Olech, Jake Fitzsimmons, Mohammad Nazmul Haque, Claudio Sanhueza Lobos, Mario Inostroza-Ponta, Regina Berretta, Luke Mathieson, Haoyuan Sun, Kevin Huang, Julia Sloan, Jon C de Oliveira, Hugh Craig, Gabriel Egan, Jonathon Corrales de Oliveira, Bo Zhang, Hongyu Zhang, Junjie Chen, Dan Hao,

Genetic Programming Articles by Pablo Moscato

  1. Pablo Moscato and Hugh Craig and Gabriel Egan and Mohammad Nazmul Haque and Kevin Huang and Julia Sloan and Jonathon Corrales de Oliveira. Multiple regression techniques for modelling dates of first performances of Shakespeare-era plays. Expert Systems with Applications, 200:116903, 2022. details

  2. Pablo Moscato and Haoyuan Sun and Mohammad Nazmul Haque. Analytic Continued Fractions for Regression: A Memetic Algorithm Approach. Expert Systems with Applications, 179:115018, 2021. details

  3. Natalie Jane de Vries and Rodrigo Reis and Pablo Moscato. Clustering Consumers Based on Trust, Confidence and Giving Behaviour: Data-Driven Model Building for Charitable Involvement in the Australian Not-For-Profit Sector. PLOS ONE, 10(4) 2015. details

  4. Natalie Jane de Vries and Jamie Carlson and Pablo Moscato. A Data-Driven Approach to Reverse Engineering Customer Engagement Models: Towards Functional Constructs. PLOS ONE, 9(7) 2014. details

Genetic Programming conference papers by Pablo Moscato

  1. Pablo Moscato and Haoyuan Sun and Mohammad Nazmul Haque. Analytic Continued Fractions for Regression: Results on 352 datasets from the physical sciences. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation, CEC 2020, internet, 2020. IEEE Press. details

  2. Bo Zhang and Hongyu Zhang and Junjie Chen and Dan Hao and Pablo Moscato. Automatic Discovery and Cleansing of Numerical Metamorphic Relations. In Miryung Kim and Arpad Beszedes editors, 35th IEEE International Conference on Software Maintenance and Evolution (ICSME, 2019), pages 235-245, Cleveland, USA, 2019. details

  3. Haoyuan Sun and Pablo Moscato. A Memetic Algorithm for Symbolic Regression. In 2019 IEEE Congress on Evolutionary Computation (CEC), pages 2167-2174, Wellington, New Zealand, 2019. details

  4. Jake Fitzsimmons and Pablo Moscato. Symbolic Regression Modeling of Drug Responses. In 2018 First International Conference on Artificial Intelligence for Industries (AI4I), pages 52-59, Laguna Hills, CA, USA, 2018. details

  5. Carlos Cotta and Pablo Moscato. Inferring Phylogenetic Trees Using Evolutionary Algorithms. In Juan J. Merelo-Guervos and Panagiotis Adamidis and Hans-Georg Beyer and Jose-Luis Fernandez-Villacanas and Hans-Paul Schwefel editors, Parallel Problem Solving from Nature - PPSN VII, pages 720-729, Granada, Spain, 2002. Springer-Verlag. details

Genetic Programming book chapters by Pablo Moscato

  1. Natalie Jane de Vries and Jamie Carlson and Pablo Moscato. Clustering Consumers and Cluster-Specific Behavioural Models. In Pablo Moscato and Natalie Jane de Vries editors, Business and Consumer Analytics: New Ideas, chapter 5, pages 235-267. Springer International Publishing, 2019. details

  2. Natalie Jane de Vries and Lukasz P. Olech and Pablo Moscato. Introducing Clustering with a Focus in Marketing and Consumer Analysis. In Pablo Moscato and Natalie Jane de Vries editors, Business and Consumer Analytics: New Ideas, chapter 3, pages 165-212. Springer International Publishing, 2019. details

  3. Natalie Jane de Vries and Pablo Moscato. Consumer Behaviour and Marketing Fundamentals for Business Data Analytics. In Pablo Moscato and Natalie Jane de Vries editors, Business and Consumer Analytics: New Ideas, chapter 2, pages 119-162. Springer International Publishing, 2019. details

  4. Pablo Moscato and Natalie Jane de Vries. Marketing Meets Data Science: Bridging the Gap. In Pablo Moscato and Natalie Jane de Vries editors, Business and Consumer Analytics: New Ideas, chapter 1, pages 3-117. Springer International Publishing, 2019. details

  5. Luke Mathieson and Natalie Jane de Vries and Pablo Moscato. Using Network Alignment to Identify Conserved Consumer Behaviour Modelling Constructs. In Pablo Moscato and Natalie Jane de Vries editors, Business and Consumer Analytics: New Ideas, chapter 12, pages 513-541. Springer International Publishing, 2019. details

  6. Claudio Sanhueza Lobos and Natalie Jane de Vries and Mario Inostroza-Ponta and Regina Berretta and Pablo Moscato. Visualizing Products and Consumers: A Gestalt Theory Inspired Method. In Pablo Moscato and Natalie Jane de Vries editors, Business and Consumer Analytics: New Ideas, chapter 16, pages 661-689. Springer International Publishing, 2019. details

  7. Mohammad Nazmul Haque and Natalie Jane de Vries and Pablo Moscato. A Multi-objective Meta-Analytic Method for Customer Churn Prediction. In Pablo Moscato and Natalie Jane de Vries editors, Business and Consumer Analytics: New Ideas, chapter 20, pages 781-813. Springer International Publishing, 2019. details

Genetic Programming other entries for Pablo Moscato