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ORCIDJosé Ramón Quevedo
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2020 – today
- 2024
[i5]Miriam Fdez-Díaz, José Ramón Quevedo, Elena Montañés:
Target inductive methods for zero-shot regression. CoRR abs/2402.01252 (2024)- [i4]Miriam Fdez-Díaz, Elena Montañés, José Ramón Quevedo:
Direct side information learning for zero-shot regression. CoRR abs/2402.01264 (2024) - [i3]Laura Fdez-Díaz, José Ramón Quevedo, Elena Montañés:
Regularized boosting with an increasing coefficient magnitude stop criterion as meta-learner in hyperparameter optimization stacking ensemble. CoRR abs/2402.01379 (2024) - [i2]Laura Fdez-Díaz, Sara González Tomillo, Elena Montañés, José Ramón Quevedo:
Improving importance estimation in covariate shift for providing accurate prediction error. CoRR abs/2402.01450 (2024) - [i1]Laura Fernández Díaz, Miriam Fernández Díaz, José Ramón Quevedo, Elena Montañés:
Capturing waste collection planning expert knowledge in a fitness function through preference learning. CoRR abs/2402.01849 (2024) - 2023
- [j22]Laura Fdez-Díaz, José Ramón Quevedo, Elena Montañés:
Regularized boosting with an increasing coefficient magnitude stop criterion as meta-learner in hyperparameter optimization stacking ensemble. Neurocomputing 551: 126516 (2023) - [j21]Miriam Fdez-Díaz
, Elena Montañés, José Ramón Quevedo:
Direct side information learning for zero-shot regression. Neurocomputing 561: 126873 (2023) - 2022
- [j20]Laura Fdez-Díaz, Sara Glez-Tomillo, Elena Montañés, José Ramón Quevedo:
Improving importance estimation in covariate shift for providing accurate prediction error. Expert Syst. Appl. 193: 116376 (2022) - [j19]Miriam Fdez-Díaz, José Ramón Quevedo, Elena Montañés:
Target inductive methods for zero-shot regression. Inf. Sci. 599: 44-63 (2022) - 2021
- [j18]Laura Fdez-Díaz, Miriam Fdez-Díaz, José Ramón Quevedo, Elena Montañés:
Capturing waste collection planning expert knowledge in a fitness function through preference learning. Eng. Appl. Artif. Intell. 99: 104113 (2021) - 2020
- [j17]Miriam Fdez-Díaz, Laura Fdez-Díaz, Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz:
Improving the ε-approximate algorithm for Probabilistic Classifier Chains. Knowl. Inf. Syst. 62(7): 2709-2738 (2020)
2010 – 2019
- 2019
- [j16]Pablo Pérez-Gállego, Alberto Castaño, José Ramón Quevedo, Juan José del Coz:
Dynamic ensemble selection for quantification tasks. Inf. Fusion 45: 1-15 (2019) - 2017
- [j15]Pablo Pérez-Gállego, José Ramón Quevedo, Juan José del Coz:
Using ensembles for problems with characterizable changes in data distribution: A case study on quantification. Inf. Fusion 34: 87-100 (2017) - [j14]Deiner Mena, José Ramón Quevedo, Elena Montañés, Juan José del Coz:
A heuristic in A* for inference in nonlinear Probabilistic Classifier Chains. Knowl. Based Syst. 126: 78-90 (2017) - [j13]Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz:
A family of admissible heuristics for A* to perform inference in probabilistic classifier chains. Mach. Learn. 106(1): 143-169 (2017) - 2016
- [j12]Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz:
An overview of inference methods in probabilistic classifier chains for multilabel classification. WIREs Data Mining Knowl. Discov. 6(6): 215-230 (2016) - 2015
- [c20]Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz:
Using A* for Inference in Probabilistic Classifier Chains. IJCAI 2015: 3707-3713 - 2014
- [j11]Elena Montañés, Ana Suárez-Vázquez, José Ramón Quevedo:
Ordinal classification/regression for analyzing the influence of superstars on spectators in cinema marketing. Expert Syst. Appl. 41(18): 8101-8111 (2014) - [j10]Elena Montañés, Robin Senge, José Barranquero, José Ramón Quevedo, Juan José del Coz, Eyke Hüllermeier:
Dependent binary relevance models for multi-label classification. Pattern Recognit. 47(3): 1494-1508 (2014) - 2013
- [j9]José Antonio Sánchez del Rivero, Elena Montañés-Roces, Begoña de la Roza-Delgado, Ana Soldado, Oscar Luaces, José Ramón Quevedo, Antonio Bahamonde:
Feature selection for classification of animal feed ingredients from near infrared microscopy spectra. Inf. Sci. 241: 58-69 (2013) - 2012
- [j8]José Ramón Quevedo, Oscar Luaces, Antonio Bahamonde:
Multilabel classifiers with a probabilistic thresholding strategy. Pattern Recognit. 45(2): 876-883 (2012) - [j7]José Ramón Quevedo, Antonio Bahamonde, Miguel Pérez-Enciso, Oscar Luaces:
Disease Liability Prediction from Large Scale Genotyping Data Using Classifiers with a Reject Option. IEEE ACM Trans. Comput. Biol. Bioinform. 9(1): 88-97 (2012) - 2011
- [j6]Elena Montañés, José Ramón Quevedo, Maria M. Prieto:
A greedy algorithm for dimensionality reduction in polynomial regression to forecast the performance of a power plant condenser. Intell. Data Anal. 15(5): 733-748 (2011) - [j5]Elena Montañés, José Ramón Quevedo, Irene Díaz, Raquel Cortina, Pedro Alonso, José Ranilla:
TagRanker: learning to recommend ranked tags. Log. J. IGPL 19(2): 395-404 (2011) - [c19]Gerardo Lastra, Oscar Luaces, José Ramón Quevedo, Antonio Bahamonde:
Graphical Feature Selection for Multilabel Classification Tasks. IDA 2011: 246-257 - [c18]Elena Montañés, José Ramón Quevedo, Juan José del Coz:
Aggregating Independent and Dependent Models to Learn Multi-label Classifiers. ECML/PKDD (2) 2011: 484-500 - 2010
- [j4]Oscar Luaces, José Ramón Quevedo, Miguel Pérez-Enciso, Jorge Díez, Juan José del Coz, Antonio Bahamonde:
Explaining the Genetic Basis of Complex Quantitative Traits through Prediction Models. J. Comput. Biol. 17(12): 1711-1723 (2010) - [c17]José Ramón Quevedo, Elena Montañés, José Ranilla, Irene Díaz:
Ranked Tag Recommendation Systems Based on Logistic Regression. HAIS (1) 2010: 237-244 - [c16]Oscar Luaces, Luiz Henrique A. Rodrigues, Carlos Alberto Alves Meira, José Ramón Quevedo, Antonio Bahamonde:
Viability of an Alarm Predictor for Coffee Rust Disease Using Interval Regression. IEA/AIE (2) 2010: 337-346 - [c15]José Ramón Quevedo, Elena Montañés, Oscar Luaces, Juan José del Coz:
Adapting Decision DAGs for Multipartite Ranking. ECML/PKDD (3) 2010: 115-130
2000 – 2009
- 2009
- [c14]José Ramón Quevedo, Elena Montañés:
Obtaining weights of a rubric through a pairwise learning model when the assessment process involves more than one lecturer. EDM 2009: 289-298 - [c13]Antonio Bahamonde, Jaime Alonso, Juan José del Coz, Jorge Díez, José Ramón Quevedo, Oscar Luaces:
Prediction and Inheritance of Phenotypes. IWINAC (1) 2009: 275-284 - [c12]Elena Montañés, José Ramón Quevedo, Irene Díaz, José Ranilla:
Collaborative Tag Recommendation System based on Logistic Regression. DC@PKDD/ECML 2009 - 2007
- [j3]José Ramón Quevedo, Antonio Bahamonde, Oscar Luaces:
A simple and efficient method for variable ranking according to their usefulness for learning. Comput. Stat. Data Anal. 52(1): 578-595 (2007) - [j2]Elena Montañés, José Ramón Quevedo, Elías F. Combarro, Irene Díaz, José Ranilla:
A Hybrid Feature Selection Method for Text Categorization. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 15(2): 133-151 (2007) - [c11]Oscar Luaces, José Ramón Quevedo, Francisco Taboada, Guillermo M. Albaiceta, Antonio Bahamonde:
Prediction of Probability of Survival in Critically Ill Patients Optimizing the Area under the ROC Curve. IJCAI 2007: 956-961 - 2004
- [c10]Jorge Díez, Gustavo F. Bayón, José Ramón Quevedo, Juan José del Coz, Oscar Luaces, Jaime Alonso, Antonio Bahamonde:
Discovering Relevancies in Very Difficult Regression Problems: Applications to Sensory Data Analysis. ECAI 2004: 993-994 - [c9]Oscar Luaces, Gustavo F. Bayón, José Ramón Quevedo, Jorge Díez, Juan José del Coz, Antonio Bahamonde:
Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection. ECML 2004: 286-297 - [c8]Elena Montañés, Elías F. Combarro, Irene Díaz, José Ranilla, José Ramón Quevedo:
Words as Rules: Feature Selection in Text Categorization. International Conference on Computational Science 2004: 666-669 - [c7]Antonio Bahamonde, Gustavo F. Bayón, Jorge Díez, José Ramón Quevedo, Oscar Luaces, Juan José del Coz, Jaime Alonso, Félix Goyache:
Feature subset selection for learning preferences: a case study. ICML 2004 - 2003
- [c6]Elena Montañés, José Ramón Quevedo, Irene Díaz:
A Wrapper Approach with Support Vector Machines for Text Categorization. IWANN (1) 2003: 230-237 - [c5]José Ramón Quevedo, Elías F. Combarro, Antonio Bahamonde:
Choosing among Algorithms to Improve Accuracy. IWANN (1) 2003: 246-253 - 2002
- [c4]José Ramón Quevedo Pérez, María Dolores García, Elena Montañés:
Filtering Noisy Continuous Labeled Examples. IBERAMIA 2002: 50-59 - [c3]Elena Montañés, José Ramón Quevedo, Maria M. Prieto, César O. Menéndez:
Forecasting Time Series Combining Machine Learning and Box-Jenkins Time Series. IBERAMIA 2002: 491-499 - 2000
- [j1]F. López, Félix Goyache, José Ramón Quevedo, Jaime Alonso, José Ranilla, Oscar Luaces, Antonio Bahamonde, Juan José del Coz:
Un sistema inteligente para calificar morfológicamente a bovinos de la raza Asturiana de los Valles. Inteligencia Artif. 4(10): 5-17 (2000)
1990 – 1999
- 1999
- [c2]Oscar Luaces, Juan José del Coz, José Ramón Quevedo, Jaime Alonso, José Ranilla, Antonio Bahamonde:
Autonomous Clustering for Machine Learning. IWANN (1) 1999: 497-506 - [c1]Juan José del Coz, Oscar Luaces, José Ramón Quevedo, Jaime Alonso, José Ranilla, Antonio Bahamonde:
Self-Organizing Cases to Find Paradigms. IWANN (1) 1999: 527-536
Coauthor Index
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last updated on 2024-06-10 20:32 CEST by the dblp team
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