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Borja Calvo
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Journal Articles
- 2022
- [j18]Ari Urkullu
, Aritz Pérez
, Borja Calvo
:
Are the statistical tests the best way to deal with the biomarker selection problem? Knowl. Inf. Syst. 64(6): 1549-1570 (2022) - [j17]Jose Luis Flores
, Borja Calvo, Aritz Pérez
:
Non-parametric discretization for probabilistic labeled data. Pattern Recognit. Lett. 161: 52-58 (2022) - [j16]Jairo Rojas-Delgado
, Josu Ceberio
, Borja Calvo, José Antonio Lozano:
Bayesian Performance Analysis for Algorithm Ranking Comparison. IEEE Trans. Evol. Comput. 26(6): 1281-1292 (2022) - 2021
- [j15]Ari Urkullu
, Aritz Pérez
, Borja Calvo
:
Statistical model for reproducibility in ranking-based feature selection. Knowl. Inf. Syst. 63(2): 379-410 (2021) - 2019
- [j14]Ari Urkullu, Aritz Pérez, Borja Calvo
:
On the evaluation and selection of classifier learning algorithms with crowdsourced data. Appl. Soft Comput. 80: 832-844 (2019) - [j13]Josu Ceberio
, Borja Calvo
, Alexander Mendiburu
, José Antonio Lozano:
Multi-Objectivising Combinatorial Optimisation Problems by Means of Elementary Landscape Decompositions. Evol. Comput. 27(2): 291-311 (2019) - [j12]Jose Luis Flores
, Borja Calvo
, Aritz Pérez:
Supervised non-parametric discretization based on Kernel density estimation. Pattern Recognit. Lett. 128: 496-504 (2019) - 2016
- [j11]Borja Calvo, Guzmán Santafé:
scmamp: Statistical Comparison of Multiple Algorithms in Multiple Problems. R J. 8(1): 248 (2016) - 2015
- [j10]Christian Blum
, Borja Calvo
:
A matheuristic for the minimum weight rooted arborescence problem. J. Heuristics 21(4): 479-499 (2015) - [j9]Christian Blum
, Borja Calvo
, Maria J. Blesa
:
FrogCOL and FrogMIS: new decentralized algorithms for finding large independent sets in graphs. Swarm Intell. 9(2-3): 205-227 (2015) - 2013
- [j8]Jose Luis Flores
, Iñaki Inza
, Pedro Larrañaga
, Borja Calvo
:
A new measure for gene expression biclustering based on non-parametric correlation. Comput. Methods Programs Biomed. 112(3): 367-397 (2013) - 2012
- [j7]Borja Calvo
, Iñaki Inza
, Pedro Larrañaga
, José Antonio Lozano:
Wrapper positive Bayesian network classifiers. Knowl. Inf. Syst. 33(3): 631-654 (2012) - 2011
- [j6]Ekhine Irurozki
, Borja Calvo
, José Antonio Lozano:
A Preprocessing Procedure for Haplotype Inference by Pure Parsimony. IEEE ACM Trans. Comput. Biol. Bioinform. 8(5): 1183-1195 (2011) - 2009
- [j5]Borja Calvo
, Pedro Larrañaga
, José Antonio Lozano:
Feature subset selection from positive and unlabelled examples. Pattern Recognit. Lett. 30(11): 1027-1036 (2009) - [j4]Rubén Armañanzas
, Borja Calvo
, Iñaki Inza
, Marcos López-Hoyos, Víctor Martínez-Taboada, Eduardo Ucar, Irantzu Bernales
, Asier Fullaondo
, Pedro Larrañaga
, Ana M. Zubiaga:
Microarray Analysis of Autoimmune Diseases by Machine Learning Procedures. IEEE Trans. Inf. Technol. Biomed. 13(3): 341-350 (2009) - 2007
- [j3]Borja Calvo
, Núria López-Bigas
, Simon J. Furney
, Pedro Larrañaga
, José Antonio Lozano:
A partially supervised classification approach to dominant and recessive human disease gene prediction. Comput. Methods Programs Biomed. 85(3): 229-237 (2007) - [j2]Borja Calvo
, Pedro Larrañaga
, José Antonio Lozano:
Learning Bayesian classifiers from positive and unlabeled examples. Pattern Recognit. Lett. 28(16): 2375-2384 (2007) - 2006
- [j1]Pedro Larrañaga
, Borja Calvo
, Roberto Santana, Concha Bielza
, Josu Galdiano, Iñaki Inza
, José Antonio Lozano, Rubén Armañanzas
, Guzmán Santafé, Aritz Pérez Martínez, Victor Robles
:
Machine learning in bioinformatics. Briefings Bioinform. 7(1): 86-112 (2006)
Conference and Workshop Papers
- 2020
- [c10]Maitena Tellaetxe-Abete, Borja Calvo
, Charles Lawrie:
An Iterated Local Search Algorithm for the Clonal Deconvolution Problem. CEC 2020: 1-8 - 2019
- [c9]Borja Calvo
, Ofer M. Shir, Josu Ceberio
, Carola Doerr
, Hao Wang, Thomas Bäck
, José Antonio Lozano:
Bayesian performance analysis for black-box optimization benchmarking. GECCO (Companion) 2019: 1789-1797 - 2018
- [c8]Kevin Villalobos
, Jon Vadillo, Borja Diez, Borja Calvo
, Arantza Illarramendi
:
I4TSPS: a Visual-Interactive Web System for Industrial Time-Series Pre-processing. IEEE BigData 2018: 2012-2018 - [c7]Joan Alza
, Josu Ceberio
, Borja Calvo
:
Balancing the Diversification-Intensification Trade-off Using Mixtures of Probability Models. CEC 2018: 1-8 - [c6]Borja Calvo
, Josu Ceberio
, José Antonio Lozano:
Bayesian inference for algorithm ranking analysis. GECCO (Companion) 2018: 324-325 - 2015
- [c5]Josu Ceberio
, Borja Calvo
, Alexander Mendiburu
, José Antonio Lozano:
Multi-objectivising the Quadratic Assignment Problem by Means of an Elementary Landscape Decomposition. CAEPIA 2015: 289-300 - 2014
- [c4]Christian Blum, Maria J. Blesa, Borja Calvo:
Can Frogs Find Large Independent Sets in a Decentralized Way? Yes They Can! ANTS Conference 2014: 74-85 - [c3]Konstantinos Sechidis, Borja Calvo
, Gavin Brown:
Statistical Hypothesis Testing in Positive Unlabelled Data. ECML/PKDD (3) 2014: 66-81 - 2013
- [c2]Christian Blum
, Maria J. Blesa
, Borja Calvo
:
Beam-ACO for the Repetition-Free Longest Common Subsequence Problem. Artificial Evolution 2013: 79-90 - 2011
- [c1]Ekhine Irurozki, Borja Calvo, José Antonio Lozano:
Learning Probability Distributions over Permutations by Means of Fourier Coefficients. Canadian AI 2011: 186-191
Informal and Other Publications
- 2024
- [i1]Josu Ceberio, Borja Calvo:
Time to Stop and Think: What kind of research do we want to do? CoRR abs/2402.08298 (2024)
Coauthor Index
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