Mario Graff
Mario Graff
CONACYT - INFOTEC Centro de Investigación e Innovación en Tecnologías de la
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Cited by
Cited by
Evolutive design of ARMA and ANN models for time series forecasting
JJ Flores, M Graff, H Rodriguez
Renewable Energy 44, 225-230, 2012
Term-Weighting Learning via Genetic Programming for Text Classification
HJ Escalante, MA García-Limón, A Morales-Reyes, M Graff, ...
Knowledge-Based Systems 85, 176–189, 2015
There is a free lunch for hyper-heuristics, genetic programming and computer scientists
R Poli, M Graff
European conference on genetic programming, 195-207, 2009
A simple approach to multilingual polarity classification in Twitter
ES Tellez, S Miranda-Jiménez, M Graff, D Moctezuma, RR Suárez, ...
Pattern Recognition Letters 94, 68-74, 2017
An automated text categorization framework based on hyperparameter optimization
ES Tellez, D Moctezuma, S Miranda-Jiménez, M Graff
Knowledge-Based Systems 149, 110-123, 2018
A case study of Spanish text transformations for twitter sentiment analysis
ES Tellez, S Miranda-Jiménez, M Graff, D Moctezuma, OS Siordia, ...
Expert Systems with Applications 81, 457-471, 2017
Practical performance models of algorithms in evolutionary program induction and other domains
M Graff, R Poli
Artificial Intelligence 174 (15), 1254-1276, 2010
Near neighbor searching with K nearest references
E Chavez, M Graff, G Navarro, ES Téllez
Information Systems 51, 43-61, 2015
Semantic genetic programming for sentiment analysis
M Graff, ES Tellez, HJ Escalante, S Miranda-Jiménez
NEO 2015, 43-65, 2017
Free lunches for function and program induction
R Poli, M Graff, NF McPhee
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic …, 2009
Gender and language-variety Identification with MicroTC.
ES Tellez, S Miranda-Jiménez, M Graff, D Moctezuma
CLEF (Working Notes), 2017
Wind speed forecasting using genetic programming
M Graff, R Pena, A Medina
2013 IEEE Congress on Evolutionary Computation, 408-415, 2013
EvoDAG: A Semantic Genetic Programming Python Library
M Graff, ES Tellez, S Miranda-Jiménez, HJ Escalante
2016 IEEE International Autumn Meeting on Power, Electronics and Computing …, 2016
Models of performance of time series forecasters
M Graff, HJ Escalante, J Cerda-Jacobo, AA Gonzalez
Neurocomputing 122, 375-385, 2013
Wind speed forecasting using a portfolio of forecasters
M Graff, R Pena, A Medina, HJ Escalante
Renewable Energy 68, 550-559, 2014
Predicting concrete compressive strength and modulus of rupture using different NDT techniques
W Martínez-Molina, AA Torres-Acosta, JC Jáuregui, HL Chávez-García, ...
Advances in Materials Science and Engineering 2014, 2014
Practical model of genetic programming’s performance on rational symbolic regression problems
M Graff, R Poli
European Conference on Genetic Programming, 122-133, 2008
Wind prediction using genetic programming and gene expression programming
JJ Flores, M Graff, E Cadena
Techniques and Methodologies for Modelling and Simulation of Systems, Lyon …, 2005
MOPG: a multi-objective evolutionary algorithm for prototype generation
HJ Escalante, M Marin-Castro, A Morales-Reyes, M Graff, ...
Pattern Analysis and Applications 20 (1), 33-47, 2017
Models of performance of evolutionary program induction algorithms based on indicators of problem difficulty
M Graff, R Poli, JJ Flores
Evolutionary computation 21 (4), 533-560, 2013
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