Genetic Programming Bibliography entries for Jose Manuel Velasco Cabo

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GP coauthors/coeditors: J Manuel Colmenar, Jose Ignacio Hidalgo Perez, J Lanchares, Oscar Garnica, Jose L Risco-Martin, Ivan Contreras, Almudena Sanchez, Sergio Contador, Carlos Cervigon Ruckauer, Carlos Garcia Sanchez, Guillermo Botella, Gabriel Kronberger, Stephan M Winkler, Marta Botella-Serrano, Remedios Martinez, Aranzazu Aramendi, Esther Maqueda, Daniel Parra Rodriguez, David Joedicke, Alberto Gutierrez, Alberto Gutierrez-Gallego, Rafael-Jacinto Villanueva, Jose Antonio Rubio,

Genetic Programming Articles by Jose Manuel Velasco Cabo

  1. Sergio Contador and J. Manuel Colmenar and Oscar Garnica and J. Manuel Velasco and J. Ignacio Hidalgo. Blood glucose prediction using multi-objective grammatical evolution: analysis of the ``agnostic'' and ``what-if'' scenarios. Genetic Programming and Evolvable Machines, 23(2):161-192, 2022. details

  2. Sergio Contador and J. Manuel Velasco and Oscar Garnica and J. Ignacio Hidalgo. Glucose forecasting using genetic programming and latent glucose variability features. Applied Soft Computing, 110:107609, 2021. details

  3. Jose Ignacio Hidalgo and Marta Botella and J. Manuel Velasco and Oscar Garnica and Carlos Cervigon and Remedios Martinez and Aranzazu Aramendi and Esther Maqueda and Juan Lanchares. Glucose forecasting combining Markov chain based enrichment of data, random grammatical evolution and Bagging. Appl. Soft Comput, 88:105923, 2020. details

  4. Jose Manuel Velasco and Oscar Garnica and Juan Lanchares and Marta Botella and J. Ignacio Hidalgo. Combining data augmentation, EDAs and grammatical evolution for blood glucose forecasting. Memetic Computing, 10(3):267-277, 2018. details

Genetic Programming conference papers by Jose Manuel Velasco Cabo

  1. Daniel Parra and Alberto Gutierrez-Gallego and Jose Manuel Velasco and Rafael-Jacinto Villanueva and J. Ignacio Hidalgo. Modelling the Transmission Dynamics of Obesity: A Multi-Objective Approach Using Dynamic Structured Grammatical Evolution. In Justyna Petke and Aniko Ekart editors, Proceedings of the 2023 Genetic and Evolutionary Computation Conference, pages 73-74, Lisbon, Portugal, 2023. Association for Computing Machinery. details

  2. J. Ignacio Hidalgo and Jose Manuel Velasco and Daniel Parra and Oscar Garnica. Genetic Programming Techniques for Glucose Prediction in People with Diabetes. In Stephan Winkler and Leonardo Trujillo and Charles Ofria and Ting Hu editors, Genetic Programming Theory and Practice XX, pages 105-124, Michigan State University, USA, 2023. Springer. details

  3. Daniel Parra and Alberto Gutierrez and Jose-Manuel Velasco and Oscar Garnica and J. Ignacio Hidalgo. Combining the Properties of Random Forest with Grammatical Evolution to Construct Ensemble Models. In Juan Luis Jimenez Laredo and J. Ignacio Hidalgo and Kehinde Oluwatoyin Babaagba editors, 25th International Conference, EvoApplications 2022, volume 13224, pages 61-76, Madrid, 2022. Springer. details

  4. David Joedicke and Gabriel Kronberger and Jose Manuel Colmenar and Stephan M. Winkler and Jose Manuel Velasco and Sergio Contador and Jose Ignacio Hidalgo. Analysis of the performance of Genetic Programming on the Blood Glucose Level Prediction Challenge 2020. In Kerstin Bach and Razvan C. Bunescu and Cindy Marling and Nirmalie Wiratunga editors, Proceedings of the 5th International Workshop on Knowledge Discovery in Healthcare Data co-located with 24th European Conference on Artificial Intelligence, KDH@ECAI 2020, volume 2675, pages 141-145, Santiago de Compostela, Spain and Virtually, 2020. CEUR-WS.org. details

  5. Sergio Contador and J. Manuel Velasco and Oscar Garnica and J. Ignacio Hidalgo. Profiled Glucose Forecasting using Genetic Programming and Clustering. In Federico Divina and Miguel Garcia Torres editors, The 35th ACM/SIGAPP Symposium On Applied Computing, pages 529-536, Brno, Czech Republic, 2020. ACM. details

  6. Sergio Contador and J. Ignacio Hidalgo and Oscar Garnica and J. Manuel Velasco and Juan Lanchares. Can clustering improve glucose forecasting with genetic programming models?. In Richard Allmendinger and Carlos Cotta and Carola Doerr and Pietro S. Oliveto and Thomas Weise and Ales Zamuda and Anne Auger and Dimo Brockhoff and Nikolaus Hansen and Tea Tusar and Konstantinos Varelas and David Camacho-Fernandez and Massimiliano Vasile and Annalisa Riccardi and Bilel Derbel and Ke Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Ozgur Akman and Khulood Alyahya and Juergen Branke and Jonathan Fieldsend and Tinkle Chugh and Jussi Hakanen and Josu Ceberio Uribe and Valentino Santucci and Marco Baioletti and John McCall and Emma Hart and Daniel R. Tauritz and John R. Woodward and Koichi Nakayama and Chika Oshima and Stefan Wagner and Michael Affenzeller and Eneko Osaba and Javier Del Ser and Pascal Kerschke and Boris Naujoks and Vanessa Volz and Anna I Esparcia-Alcazar and Riyad Alshammari and Erik Hemberg and Tokunbo Makanju and Brad Alexander and Saemundur O. Haraldsson and Markus Wagner and Silvino Fernandez Alzueta and Pablo Valledor Pellicer and Thomas Stuetzle and David Walker and Matt Johns and Nick Ross and Ed Keedwell and Masaya Nakata and Anthony Stein and Takato Tatsumi and Nadarajen Veerapen and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa and Stephen Smith and Stefano Cagnoni and Robert M. Patton and William La Cava and Randal Olson and Patryk Orzechowski and Ryan Urbanowicz and Akira Oyama and Koji Shimoyama and Hemant Kumar Singh and Kazuhisa Chiba and Pramudita Satria Palar and Alma Rahat and Richard Everson and Handing Wang and Yaochu Jin and Marcus Gallagher and Mike Preuss and Olivier Teytaud and Fernando Lezama and Joao Soares and Zita Vale editors, GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 1829-1836, Prague, Czech Republic, 2019. ACM. details

  7. Jose Manuel Velasco and Oscar Garnica and Sergio Contador and Juan Lanchares and Esther Maqueda and Marta Botella and J. Ignacio Hidalgo. Data augmentation and evolutionary algorithms to improve the prediction of blood glucose levels in scarcity of training data. In Jose A. Lozano editor, 2017 IEEE Congress on Evolutionary Computation (CEC), pages 2193-2200, Donostia, San Sebastian, Spain, 2017. IEEE. details

  8. Jose Manuel Velasco and Oscar Garnica and Sergio Contador and Jose Manuel Colmenar and Esther Maqueda and Marta Botella and Juan Lanchares and Jose Ignacio Hidalgo. Enhancing Grammatical Evolution Through Data Augmentation: Application to Blood Glucose Forecasting. In Giovanni Squillero editor, 20th European Conference on the Applications of Evolutionary Computation, volume 10199, pages 142-157, Amsterdam, 2017. Springer. details

  9. Jose Ignacio Hidalgo and Carlos Cervigon and Jose Manuel Velasco and J. Manuel Colmenar and Carlos Garcia Sanchez and Guillermo Botella. Embedded Grammars for Grammatical Evolution on GPGPU. In Giovanni Squillero editor, 20th European Conference on the Applications of Evolutionary Computation, volume 10199, pages 789-805, Amsterdam, 2017. Springer. details

  10. J. Manuel Colmenar and Jose Ignacio Hidalgo and Juan Lanchares and Oscar Garnica and Jose L. Risco-Martin and Ivan Contreras and Almudena Sanchez and J. Manuel Velasco. Compilable Phenotypes: Speeding-Up the Evaluation of Glucose Models in Grammatical Evolution. In Giovanni Squillero and Paolo Burelli editors, 19th European Conference on Applications of Evolutionary Computation, EvoApplications 2016, volume 9598, pages 118-133, Porto, Portugal, 2016. Springer. details

  11. J. Manuel Velasco and Stephan Winkler and J. Ignacio Hidalgo and Oscar Garnica and Juan Lanchares and J. Manuel Colmenar and Esther Maqueda and Marta Botella and Jose-Antonio Rubio. Data-Based Identification of Prediction Models for Glucose. In Stephen L. Smith and Stefano Cagnoni and Robert M. Patton editors, GECCO 2015 Medical Applications of Genetic and Evolutionary Computation (MedGEC'15) Workshop, pages 1327-1334, Madrid, Spain, 2015. ACM. details

Genetic Programming book chapters by Jose Manuel Velasco Cabo