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ORCIDAritz Pérez Martínez
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2020 – today
- 2025
[j36]Judith Echevarrieta
, Etor Arza, Aritz Pérez:
Speeding-Up Evolutionary Algorithms to Solve Black-Box Optimization Problems. IEEE Trans. Evol. Comput. 29(1): 117-131 (2025)- 2024
- [j35]Onintze Zaballa, Aritz Pérez, Elisa Gómez-Inhiesto, Teresa Acaiturri Ayesta, José Antonio Lozano:
A probabilistic generative model to discover the treatments of coexisting diseases with missing data. Comput. Methods Programs Biomed. 243: 107870 (2024) - [j34]Carlos Echegoyen, Aritz Pérez, Guzmán Santafé, Unai Pérez-Goya, María Dolores Ugarte:
Large-scale unsupervised spatio-temporal semantic analysis of vast regions from satellite images sequences. Stat. Comput. 34(2): 71 (2024) - [j33]Marco Capó, Aritz Pérez, José Antonio Lozano:
Fast $K$-Medoids With the $l_{1}$-Norm. IEEE Trans. Artif. Intell. 5(4): 1769-1777 (2024) - [c20]Ioar Casado, Luis A. Ortega Andrés, Aritz Pérez, Andrés R. Masegosa:
PAC-Bayes-Chernoff bounds for unbounded losses. NeurIPS 2024 - [i21]Ioar Casado, Luis A. Ortega, Andrés R. Masegosa, Aritz Pérez:
PAC-Bayes-Chernoff bounds for unbounded losses. CoRR abs/2401.01148 (2024) - [i20]Aritz Pérez, Carlos Echegoyen, Guzmán Santafé:
Risk-based Calibration for Probabilistic Classifiers. CoRR abs/2409.03542 (2024) - 2023
- [j32]Onintze Zaballa, Aritz Pérez, Elisa Gómez-Inhiesto, Teresa Acaiturri Ayesta, José Antonio Lozano:
Learning the progression patterns of treatments using a probabilistic generative model. J. Biomed. Informatics 137: 104271 (2023) - [j31]Etor Arza, Josu Ceberio, Ekhiñe Irurozki, Aritz Pérez:
Comparing Two Samples Through Stochastic Dominance: A Graphical Approach. J. Comput. Graph. Stat. 32(2): 551-566 (2023) - [j30]Iker Beñaran-Muñoz, Jerónimo Hernández-González, Aritz Pérez:
On the use of the descriptive variable for enhancing the aggregation of crowdsourced labels. Knowl. Inf. Syst. 65(1): 241-260 (2023) - [j29]Marco Capó, Aritz Pérez, José Antonio Lozano:
Fast computation of cluster validity measures for bregman divergences and benefits. Pattern Recognit. Lett. 170: 100-105 (2023) - [j28]Marco Capó, Aritz Pérez, José Antonio Lozano:
LASSO for streaming data with adaptative filtering. Stat. Comput. 33(1): 5 (2023) - [c19]Kartheek Bondugula, Santiago Mazuelas, Aritz Pérez:
Efficient Learning of Minimax Risk Classifiers in High Dimensions. UAI 2023: 206-215 - [i19]Etor Arza, Josu Ceberio, Ekhiñe Irurozki, Aritz Pérez:
On the Fair Comparison of Optimization Algorithms in Different Machines. CoRR abs/2305.07345 (2023) - [i18]Kartheek Bondugula, Santiago Mazuelas, Aritz Pérez:
Efficient Learning of Minimax Risk Classifiers in High Dimensions. CoRR abs/2306.06649 (2023) - [i17]Arkaitz Bidaurrazaga, Aritz Pérez, Roberto Santana:
Structural Restricted Boltzmann Machine for image denoising and classification. CoRR abs/2306.09628 (2023) - [i16]Judith Echevarrieta, Etor Arza, Aritz Pérez:
Speeding-up Evolutionary Algorithms to solve Black-Box Optimization Problems. CoRR abs/2309.13349 (2023) - [i15]Onintze Zaballa, Aritz Pérez, Elisa Gómez-Inhiesto, Teresa Acaiturri Ayesta, José Antonio Lozano:
Time-dependent Probabilistic Generative Models for Disease Progression. CoRR abs/2311.09369 (2023) - 2022
- [j27]Iker Beñaran-Muñoz, Jerónimo Hernández-González, Aritz Pérez:
Machine Learning From Crowds Using Candidate Set-Based Labeling. IEEE Intell. Syst. 37(6): 57-68 (2022) - [j26]Jerónimo Hernández-González, Aritz Pérez:
On the relative value of weak information of supervision for learning generative models: An empirical study. Int. J. Approx. Reason. 150: 258-272 (2022) - [j25]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) - [j24]Izaskun Oregi, Aritz Pérez, Javier Del Ser, José Antonio Lozano:
An active adaptation strategy for streaming time series classification based on elastic similarity measures. Neural Comput. Appl. 34(16): 13237-13252 (2022) - [j23]Jose Luis Flores, Borja Calvo, Aritz Pérez:
Non-parametric discretization for probabilistic labeled data. Pattern Recognit. Lett. 161: 52-58 (2022) - [j22]Santiago Mazuelas, Yuan Shen, Aritz Pérez:
Generalized Maximum Entropy for Supervised Classification. IEEE Trans. Inf. Theory 68(4): 2530-2550 (2022) - [j21]Marco Capó, Aritz Pérez, José Antonio Lozano:
An Efficient Split-Merge Re-Start for the $K$K-Means Algorithm. IEEE Trans. Knowl. Data Eng. 34(4): 1618-1627 (2022) - [c18]Etor Arza, Josu Ceberio, Ekhiñe Irurozki, Aritz Pérez:
Implementing the cumulative difference plot in the IOHanalyzer. GECCO Companion 2022: 11-12 - [c17]Ioar Casado, Aritz Pérez:
Dirichlet process mixture models for non-stationary data streams. ICDM 2022: 873-878 - [i14]Etor Arza, Josu Ceberio, Ekhiñe Irurozki, Aritz Pérez:
Comparing two samples through stochastic dominance: a graphical approach. CoRR abs/2203.07889 (2022) - [i13]Carlos Echegoyen, Aritz Pérez, Guzmán Santafé, Unai Pérez-Goya, María Dolores Ugarte:
Semantic Clustering of a Sequence of Satellite Images. CoRR abs/2208.13504 (2022) - [i12]Ioar Casado, Aritz Pérez:
Dirichlet process mixture models for non-stationary data streams. CoRR abs/2210.06872 (2022) - 2021
- [j20]Ari Urkullu, Aritz Pérez, Borja Calvo:
Statistical model for reproducibility in ranking-based feature selection. Knowl. Inf. Syst. 63(2): 379-410 (2021) - [j19]Marco Capó, Aritz Pérez, José Antonio Lozano:
A Cheap Feature Selection Approach for the K-Means Algorithm. IEEE Trans. Neural Networks Learn. Syst. 32(5): 2195-2208 (2021) - [c16]Arkaitz Bidaurrazaga, Aritz Pérez, Marco Capó:
K-means for Evolving Data Streams. ICDM 2021: 1006-1011 - [c15]Ekhine Irurozki, Aritz Pérez, Jesus L. Lobo, Javier Del Ser:
Rank Aggregation for Non-stationary Data Streams. ECML/PKDD (3) 2021: 297-313 - [i11]Kartheek Bondugula, Santiago Mazuelas, Aritz Pérez:
MRCpy: A Library for Minimax Risk Classifiers. CoRR abs/2108.01952 (2021) - 2020
- [j18]Marco Capó, Aritz Pérez, José Antonio Lozano:
An efficient K-means clustering algorithm for tall data. Data Min. Knowl. Discov. 34(3): 776-811 (2020) - [j17]Izaskun Oregi, Javier Del Ser, Aritz Pérez, José Antonio Lozano:
Robust image classification against adversarial attacks using elastic similarity measures between edge count sequences. Neural Networks 128: 61-72 (2020) - [j16]Etor Arza, Aritz Pérez, Ekhiñe Irurozki, Josu Ceberio:
Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem. Swarm Evol. Comput. 59: 100740 (2020) - [c14]Santiago Mazuelas, Aritz Pérez:
General Supervision via Probabilistic Transformations. ECAI 2020: 1348-1354 - [c13]Etor Arza, Josu Ceberio, Aritz Pérez, Ekhiñe Irurozki:
An adaptive neuroevolution-based hyperheuristic. GECCO Companion 2020: 111-112 - [c12]Santiago Mazuelas, Andrea Zanoni, Aritz Pérez:
Minimax Classification with 0-1 Loss and Performance Guarantees. NeurIPS 2020 - [c11]George Orfanides, Aritz Pérez:
Learning decomposable models by coarsening. PGM 2020: 317-328 - [i10]Santiago Mazuelas, Yuan Shen, Aritz Pérez:
Generalized Maximum Entropy for Supervised Classification. CoRR abs/2007.05447 (2020) - [i9]Santiago Mazuelas, Andrea Zanoni, Aritz Pérez:
Minimax Classification with 0-1 Loss and Performance Guarantees. CoRR abs/2010.07964 (2020) - [i8]Arkaitz Bidaurrazaga, Aritz Pérez, Marco Capó:
Passive Approach for the K-means Problem on Streaming Data. CoRR abs/2012.03628 (2020)
2010 – 2019
- 2019
- [j15]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) - [j14]Izaskun Oregi, Aritz Pérez, Javier Del Ser, José Antonio Lozano:
On-line Elastic Similarity Measures for time series. Pattern Recognit. 88: 506-517 (2019) - [j13]Jose Luis Flores, Borja Calvo, Aritz Pérez:
Supervised non-parametric discretization based on Kernel density estimation. Pattern Recognit. Lett. 128: 496-504 (2019) - [c10]Etor Arza, Josu Ceberio, Aritz Pérez, Ekhine Irurozki:
Approaching the quadratic assignment problem with kernels of mallows models under the hamming distance. GECCO (Companion) 2019: 141-142 - [i7]Santiago Mazuelas, Aritz Pérez:
General Supervision via Probabilistic Transformations. CoRR abs/1901.08552 (2019) - [i6]Santiago Mazuelas, Andrea Zanoni, Aritz Pérez:
Supervised classification via minimax probabilistic transformations. CoRR abs/1902.00693 (2019) - [i5]Ekhine Irurozki, Jesus L. Lobo, Aritz Pérez, Javier Del Ser:
Online Ranking with Concept Drifts in Streaming Data. CoRR abs/1910.08795 (2019) - [i4]Etor Arza, Aritz Pérez, Ekhine Irurozki, Josu Ceberio:
Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem. CoRR abs/1910.08800 (2019) - 2018
- [j12]Aritz Pérez Martínez, Eneko Osaba, Miren Nekane Bilbao, Javier Del Ser:
Let nature decide its nature: On the design of collaborative hyperheuristics for decentralized ephemeral environments. Future Gener. Comput. Syst. 88: 792-805 (2018) - [c9]Iker Beñaran-Muñoz, Jerónimo Hernández-González, Aritz Pérez:
Crowd Learning with Candidate Labeling: An EM-Based Solution. CAEPIA 2018: 13-23 - [c8]Aritz Pérez, Josu Ceberio, José Antonio Lozano:
Are the Artificially Generated Instances Uniform in Terms of Difficulty? CEC 2018: 1-8 - [c7]Izaskun Oregi, Javier Del Ser, Aritz Pérez, José Antonio Lozano:
Adversarial Sample Crafting for Time Series Classification with Elastic Similarity Measures. IDC 2018: 26-39 - [c6]Aritz Pérez, Christian Blum, José Antonio Lozano:
Approximating the maximum weighted decomposable graph problem with applications to probabilistic graphical models. PGM 2018: 320-331 - [i3]Marco Capó, Aritz Pérez, José Antonio Lozano:
An efficient K -means clustering algorithm for massive data. CoRR abs/1801.02949 (2018) - [i2]Iker Beñaran-Muñoz, Jerónimo Hernández-González, Aritz Pérez:
Weak Labeling for Crowd Learning. CoRR abs/1804.10023 (2018) - 2017
- [j11]Marco Capó, Aritz Pérez, José Antonio Lozano:
An efficient approximation to the K-means clustering for massive data. Knowl. Based Syst. 117: 56-69 (2017) - [c5]Izaskun Oregi, Javier Del Ser, Aritz Pérez, José Antonio Lozano:
Nature-inspired approaches for distance metric learning in multivariate time series classification. CEC 2017: 1992-1998 - [c4]Izaskun Oregi, Aritz Pérez, Javier Del Ser, José Antonio Lozano:
On-Line Dynamic Time Warping for Streaming Time Series. ECML/PKDD (2) 2017: 591-605 - 2016
- [j10]Aritz Pérez, Iñaki Inza, José Antonio Lozano:
Efficient approximation of probability distributions with k-order decomposable models. Int. J. Approx. Reason. 74: 58-87 (2016) - [i1]Marco Capó, Aritz Pérez, José Antonio Lozano:
An efficient K-means algorithm for Massive Data. CoRR abs/1605.02989 (2016) - 2015
- [j9]Jose A. Fernandes, Xabier Irigoien, José Antonio Lozano, Iñaki Inza, Nerea Goikoetxea, Aritz Pérez Martínez:
Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species. Ecol. Informatics 25: 35-42 (2015) - 2014
- [c3]Aritz Pérez, Christian Blum, José Antonio Lozano:
Learning Maximum Weighted (k+1)-Order Decomposable Graphs by Integer Linear Programming. Probabilistic Graphical Models 2014: 396-408 - 2013
- [j8]Jose A. Fernandes, José Antonio Lozano, Iñaki Inza, Xabier Irigoien, Aritz Pérez, Juan Diego Rodríguez:
Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting. Environ. Model. Softw. 40: 245-254 (2013) - [j7]Juan Diego Rodríguez, Aritz Pérez Martínez, José Antonio Lozano:
A general framework for the statistical analysis of the sources of variance for classification error estimators. Pattern Recognit. 46(3): 855-864 (2013) - [c2]Aritz Pérez Martínez, José Antonio Lozano, Iñaki Inza:
Multidimensional k-Interaction Classifier: Taking Advantage of All the Information Contained in Low Order Interactions. CAEPIA 2013: 393-401 - 2012
- [j6]Juan Diego Rodríguez, Aritz Pérez Martínez, David Arteta, Diego Tejedor, José Antonio Lozano:
Using Multidimensional Bayesian Network Classifiers to Assist the Treatment of Multiple Sclerosis. IEEE Trans. Syst. Man Cybern. Part C 42(6): 1705-1715 (2012) - 2010
- [j5]Juan Diego Rodríguez, Aritz Pérez Martínez, José Antonio Lozano:
Sensitivity Analysis of k-Fold Cross Validation in Prediction Error Estimation. IEEE Trans. Pattern Anal. Mach. Intell. 32(3): 569-575 (2010)
2000 – 2009
- 2009
- [j4]Aritz Pérez Martínez, Pedro Larrañaga, Iñaki Inza:
Bayesian classifiers based on kernel density estimation: Flexible classifiers. Int. J. Approx. Reason. 50(2): 341-362 (2009) - 2008
- [j3]Matej Guid, Aritz Pérez, Ivan Bratko:
How Trustworthy is Crafty's Analysis of Chess Champions? J. Int. Comput. Games Assoc. 31(3): 131-144 (2008) - 2006
- [j2]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) - [j1]Aritz Pérez Martínez, Pedro Larrañaga, Iñaki Inza:
Supervised classification with conditional Gaussian networks: Increasing the structure complexity from naive Bayes. Int. J. Approx. Reason. 43(1): 1-25 (2006) - [c1]Aritz Pérez Martínez, Pedro Larrañaga, Iñaki Inza:
Information Theory and Classification Error in Probabilistic Classifiers. Discovery Science 2006: 347-351
Coauthor Index
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last updated on 2025-03-04 22:33 CET by the dblp team
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