José Ramón Quevedo

According to our database, José Ramón Quevedo authored at least 43 papers between 1999 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Capturing waste collection planning expert knowledge in a fitness function through preference learning.

Laura Fernández Díaz, Miriam Fernández Díaz, José Ramón Quevedo, Elena Montañés

CoRR, 2024

2023

Direct side information learning for zero-shot regression.

Miriam Fdez-Díaz, Elena Montañés, José Ramón Quevedo

Neurocomputing, December, 2023

Regularized boosting with an increasing coefficient magnitude stop criterion as meta-learner in hyperparameter optimization stacking ensemble.

Laura Fdez-Díaz, José Ramón Quevedo, Elena Montañés

Neurocomputing, September, 2023

2022

Target inductive methods for zero-shot regression.

Miriam Fdez-Díaz, José Ramón Quevedo, Elena Montañés

Inf. Sci., 2022

Improving importance estimation in covariate shift for providing accurate prediction error.

Laura Fdez-Díaz, Sara Glez-Tomillo, Elena Montañés, José Ramón Quevedo

Expert Syst. Appl., 2022

2021

Capturing waste collection planning expert knowledge in a fitness function through preference learning.

Laura Fdez-Díaz, Miriam Fdez-Díaz, José Ramón Quevedo, Elena Montañés

Eng. Appl. Artif. Intell., 2021

2020

Improving the ε-approximate algorithm for Probabilistic Classifier Chains.

Miriam Fdez-Díaz, Laura Fdez-Díaz, Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz

Knowl. Inf. Syst., 2020

2019

Dynamic ensemble selection for quantification tasks.

Pablo Pérez-Gállego, Alberto Castaño, José Ramón Quevedo, Juan José del Coz

Inf. Fusion, 2019

2017

A family of admissible heuristics for A* to perform inference in probabilistic classifier chains.

Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz

Mach. Learn., 2017

A heuristic in A* for inference in nonlinear Probabilistic Classifier Chains.

Deiner Mena, José Ramón Quevedo, Elena Montañés, Juan José del Coz

Knowl. Based Syst., 2017

Using ensembles for problems with characterizable changes in data distribution: A case study on quantification.

Pablo Pérez-Gállego, José Ramón Quevedo, Juan José del Coz

Inf. Fusion, 2017

2016

An overview of inference methods in probabilistic classifier chains for multilabel classification.

Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz

WIREs Data Mining Knowl. Discov., 2016

2015

Using A* for Inference in Probabilistic Classifier Chains.

Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014

Dependent binary relevance models for multi-label classification.

Elena Montañés, Robin Senge, José Barranquero, José Ramón Quevedo, Juan José del Coz, Eyke Hüllermeier

Pattern Recognit., 2014

Ordinal classification/regression for analyzing the influence of superstars on spectators in cinema marketing.

Elena Montañés, Ana Suárez-Vázquez, José Ramón Quevedo

Expert Syst. Appl., 2014

2013

Feature selection for classification of animal feed ingredients from near infrared microscopy spectra.

José Antonio Sánchez del Rivero, Elena Montañés-Roces, Begoña de la Roza-Delgado, Ana Soldado, Oscar Luaces, José Ramón Quevedo, Antonio Bahamonde

Inf. Sci., 2013

2012

Disease Liability Prediction from Large Scale Genotyping Data Using Classifiers with a Reject Option.

José Ramón Quevedo, Antonio Bahamonde, Miguel Pérez-Enciso, Oscar Luaces

IEEE ACM Trans. Comput. Biol. Bioinform., 2012

Multilabel classifiers with a probabilistic thresholding strategy.

José Ramón Quevedo, Oscar Luaces, Antonio Bahamonde

Pattern Recognit., 2012

2011

TagRanker: learning to recommend ranked tags.

Elena Montañés, José Ramón Quevedo, Irene Díaz, Raquel Cortina, Pedro Alonso, José Ranilla

Log. J. IGPL, 2011

A greedy algorithm for dimensionality reduction in polynomial regression to forecast the performance of a power plant condenser.

Elena Montañés, José Ramón Quevedo, Maria M. Prieto

Intell. Data Anal., 2011

Aggregating Independent and Dependent Models to Learn Multi-label Classifiers.

Elena Montañés, José Ramón Quevedo, Juan José del Coz

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Graphical Feature Selection for Multilabel Classification Tasks.

Gerardo Lastra, Oscar Luaces, José Ramón Quevedo, Antonio Bahamonde

Proceedings of the Advances in Intelligent Data Analysis X - 10th International Symposium, 2011

2010

Explaining the Genetic Basis of Complex Quantitative Traits through Prediction Models.

Oscar Luaces, José Ramón Quevedo, Miguel Pérez-Enciso, Jorge Díez, Juan José del Coz, Antonio Bahamonde

J. Comput. Biol., 2010

Adapting Decision DAGs for Multipartite Ranking.

José Ramón Quevedo, Elena Montañés, Oscar Luaces, Juan José del Coz

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Viability of an Alarm Predictor for Coffee Rust Disease Using Interval Regression.

Oscar Luaces, Luiz Henrique A. Rodrigues, Carlos Alberto Alves Meira, José Ramón Quevedo, Antonio Bahamonde

Proceedings of the Trends in Applied Intelligent Systems, 2010

Ranked Tag Recommendation Systems Based on Logistic Regression.

José Ramón Quevedo, Elena Montañés, José Ranilla, Irene Díaz

Proceedings of the Hybrid Artificial Intelligence Systems, 5th International Conference, 2010

2009

Collaborative Tag Recommendation System based on Logistic Regression.

Elena Montañés, José Ramón Quevedo, Irene Díaz, José Ranilla

Proceedings of ECML PKDD (The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases) Discovery Challenge 2009, 2009

Prediction and Inheritance of Phenotypes.

Antonio Bahamonde, Jaime Alonso, Juan José del Coz, Jorge Díez, José Ramón Quevedo, Oscar Luaces

Proceedings of the Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira.s Scientific Legacy, 2009

Obtaining weights of a rubric through a pairwise learning model when the assessment process involves more than one lecturer.

José Ramón Quevedo, Elena Montañés

Proceedings of the Educational Data Mining, 2009

2007

A Hybrid Feature Selection Method for Text Categorization.

Elena Montañés, José Ramón Quevedo, Elías F. Combarro, Irene Díaz, José Ranilla

Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2007

A simple and efficient method for variable ranking according to their usefulness for learning.

José Ramón Quevedo, Antonio Bahamonde, Oscar Luaces

Comput. Stat. Data Anal., 2007

Prediction of Probability of Survival in Critically Ill Patients Optimizing the Area under the ROC Curve.

Oscar Luaces, José Ramón Quevedo, Francisco Taboada, Guillermo M. Albaiceta, Antonio Bahamonde

Proceedings of the IJCAI 2007, 2007

2004

Feature subset selection for learning preferences: a case study.

Antonio Bahamonde, Gustavo F. Bayón, Jorge Díez, José Ramón Quevedo, Oscar Luaces, Juan José del Coz, Jaime Alonso, Félix Goyache

Proceedings of the Machine Learning, 2004

Words as Rules: Feature Selection in Text Categorization.

Elena Montañés, Elías F. Combarro, Irene Díaz, José Ranilla, José Ramón Quevedo

Proceedings of the Computational Science, 2004

Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection.

Oscar Luaces, Gustavo F. Bayón, José Ramón Quevedo, Jorge Díez, Juan José del Coz, Antonio Bahamonde

Proceedings of the Machine Learning: ECML 2004, 2004

Discovering Relevancies in Very Difficult Regression Problems: Applications to Sensory Data Analysis.

Jorge Díez, Gustavo F. Bayón, José Ramón Quevedo, Juan José del Coz, Oscar Luaces, Jaime Alonso, Antonio Bahamonde

Proceedings of the 16th Eureopean Conference on Artificial Intelligence, 2004

2003

Choosing among Algorithms to Improve Accuracy.

José Ramón Quevedo, Elías F. Combarro, Antonio Bahamonde

Proceedings of the Artificial Neural Nets Problem Solving Methods, 2003

A Wrapper Approach with Support Vector Machines for Text Categorization.

Elena Montañés, José Ramón Quevedo, Irene Díaz

Proceedings of the Artificial Neural Nets Problem Solving Methods, 2003

2002

Filtering Noisy Continuous Labeled Examples.

José Ramón Quevedo Pérez, María Dolores García, Elena Montañés

Proceedings of the Advances in Artificial Intelligence, 2002

Forecasting Time Series Combining Machine Learning and Box-Jenkins Time Series.

Elena Montañés, José Ramón Quevedo, Maria M. Prieto, César O. Menéndez

Proceedings of the Advances in Artificial Intelligence, 2002

2000

Un sistema inteligente para calificar morfológicamente a bovinos de la raza Asturiana de los Valles.

F. López, Félix Goyache, José Ramón Quevedo, Jaime Alonso, José Ranilla, Oscar Luaces, Antonio Bahamonde, Juan José del Coz

Inteligencia Artif., 2000

1999

Autonomous Clustering for Machine Learning.

Oscar Luaces, Juan José del Coz, José Ramón Quevedo, Jaime Alonso, José Ranilla, Antonio Bahamonde

Proceedings of the Foundations and Tools for Neural Modeling, 1999

Self-Organizing Cases to Find Paradigms.

Juan José del Coz, Oscar Luaces, José Ramón Quevedo, Jaime Alonso, José Ranilla, Antonio Bahamonde

Proceedings of the Foundations and Tools for Neural Modeling, 1999