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José Antonio Lozano 0001
Person information
- affiliation: University of the Basque Country, Department of Computer Science and Artificial Intelligence
Other persons with the same name
- José Antonio Lozano 0002 (aka: José-Antonio Lozano-Quilis) — Technical University of Valencia (UPV), Spain
- José Antonio Lozano 0003 — Telefonica ID, Madrid, Spain
- José Antonio Lozano 0004 — Technical University of Madrid, Mechanical Engineering, Chemistry and Industrial Design Department, Spain
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2020 – today
- 2024
- [j149]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) - [j148]Gorka Kobeaga, Jairo Rojas-Delgado, María Merino, José Antonio Lozano:
A revisited branch-and-cut algorithm for large-scale orienteering problems. Eur. J. Oper. Res. 313(1): 44-68 (2024) - [j147]Josu Ceberio, Alexander Mendiburu, José Antonio Lozano:
A roadmap for solving optimization problems with estimation of distribution algorithms. Nat. Comput. 23(1): 99-113 (2024) - [j146]Imanol Unanue, María Merino, José Antonio Lozano:
Characterization of rankings generated by pseudo-Boolean functions. Swarm Evol. Comput. 86: 101540 (2024) - [j145]Marco Capó, Aritz Pérez, José Antonio Lozano:
Fast $K$-Medoids With the $l_{1}$-Norm. IEEE Trans. Artif. Intell. 5(4): 1769-1777 (2024) - [c110]Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto:
Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results. AISTATS 2024: 1198-1206 - [c109]Mikel Malagon, Josu Ceberio, José Antonio Lozano:
Self-Composing Policies for Scalable Continual Reinforcement Learning. ICML 2024 - [i28]Jon Vadillo, Roberto Santana, José Antonio Lozano, Marta Kwiatkowska:
Uncertainty-Aware Explanations Through Probabilistic Self-Explainable Neural Networks. CoRR abs/2403.13740 (2024) - [i27]Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto:
Dancing in the Shadows: Harnessing Ambiguity for Fairer Classifiers. CoRR abs/2406.19066 (2024) - [i26]Mikel Malagon, Josu Ceberio, José Antonio Lozano:
Craftium: An Extensible Framework for Creating Reinforcement Learning Environments. CoRR abs/2407.03969 (2024) - 2023
- [j144]Abolfazl Shirazi, Josu Ceberio, José Antonio Lozano:
Trajectory optimization of space vehicle in rendezvous proximity operation with evolutionary feasibility conserving techniques. Eng. Appl. Artif. Intell. 117(Part): 105523 (2023) - [j143]César Montenegro, Roberto Santana, José Antonio Lozano:
Introducing multi-dimensional hierarchical classification: Characterization, solving strategies and performance measures. Neurocomputing 533: 141-160 (2023) - [j142]Jonás Velasco, Salvador Vicencio, José Antonio Lozano, Néstor M. Cid-García:
Delineation of site-specific management zones using estimation of distribution algorithms. Int. Trans. Oper. Res. 30(4): 1703-1729 (2023) - [j141]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) - [j140]Jon Vadillo, Roberto Santana, José Antonio Lozano:
Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions. J. Mach. Learn. Res. 24: 15:1-15:42 (2023) - [j139]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) - [j138]Marco Capó, Aritz Pérez, José Antonio Lozano:
LASSO for streaming data with adaptative filtering. Stat. Comput. 33(1): 5 (2023) - [j137]Ander Carreño, Iñaki Inza, José Antonio Lozano:
SNDProb: A Probabilistic Approach for Streaming Novelty Detection. IEEE Trans. Knowl. Data Eng. 35(6): 6335-6348 (2023) - [j136]Ane Blázquez-García, Kristoffer Wickstrøm, Shujian Yu, Karl Øyvind Mikalsen, Ahcène Boubekki, Angel Conde, Usue Mori, Robert Jenssen, José Antonio Lozano:
Selective Imputation for Multivariate Time Series Datasets With Missing Values. IEEE Trans. Knowl. Data Eng. 35(9): 9490-9501 (2023) - [j135]Josu Ircio, Aizea Lojo, Usue Mori, Simon Malinowski, José Antonio Lozano:
Minimum Recall-Based Loss Function for Imbalanced Time Series Classification. IEEE Trans. Knowl. Data Eng. 35(10): 10024-10034 (2023) - [c108]Kaoutar Senhaji, Carlos A. Coello Coello, José Antonio Lozano:
An Improved Version of MMOEA/DC Based on Alternative Clustering Definitions. CEC 2023: 1-9 - [c107]Imanol Unanue, María Merino, José Antonio Lozano:
The Natural Bias of Artificial Instances. CEC 2023: 1-8 - [c106]Gia Sirbiladze, Janusz Kacprzyk, Bidzina Midodashvili, Bezhan Ghvaberidze, José Antonio Lozano, Tinatin Davitashvili:
Dependable and Resilient Emergency MAGDM Approach for the Selection of HADCs. DESSERT 2023: 1-5 - [c105]Gia Sirbiladze, Janusz Kacprzyk, Bidzina Midodashvili, Bezhan Ghvaberidze, José Antonio Lozano, Tinatin Davitashvili:
Evidence Theory and Fuzzy Discriminations in Dependable and Resilient Interactive MADM. Application in Emergency Psychiatric Diagnostics. DESSERT 2023: 1-6 - [c104]José Antonio Lozano:
Analyzing the Fourier Representation of Permutation-Based Combinatorial Optimization Problems. FOGA 2023: 1 - [c103]Xabier Benavides, Josu Ceberio, Leticia Hernando, José Antonio Lozano:
New Knowledge about the Elementary Landscape Decomposition for Solving the Quadratic Assignment Problem. GECCO 2023: 239-247 - [c102]Manuel Torralbo, Leticia Hernando, Ernesto Contreras-Torres, José Antonio Lozano:
On the Use of Second Order Neighbors to Escape from Local Optima. GECCO 2023: 375-383 - [c101]Roberto Santana, Ivan Hidalgo-Cenalmor, Unai Garciarena, Alexander Mendiburu, José Antonio Lozano:
Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification. GECCO Companion 2023: 679-682 - [c100]Verónica Álvarez, Santiago Mazuelas, José Antonio Lozano:
Minimax Forward and Backward Learning of Evolving Tasks with Performance Guarantees. NeurIPS 2023 - [i25]Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto:
Uncertainty in Fairness Assessment: Maintaining Stable Conclusions Despite Fluctuations. CoRR abs/2302.01079 (2023) - [i24]Roberto Santana, Ivan Hidalgo-Cenalmor, Unai Garciarena, Alexander Mendiburu, José Antonio Lozano:
Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification. CoRR abs/2303.02801 (2023) - [i23]Verónica Álvarez, Santiago Mazuelas, José Antonio Lozano:
Minimax Forward and Backward Learning of Evolving Tasks with Performance Guarantees. CoRR abs/2310.15974 (2023) - [i22]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
- [j134]Josu Ircio, Aizea Lojo, José Antonio Lozano, Usue Mori:
A Multivariate Time Series Streaming Classifier for Predicting Hard Drive Failures [Application Notes]. IEEE Comput. Intell. Mag. 17(1): 102-114 (2022) - [j133]Ane Blázquez-García, Angel Conde, Usue Mori, José Antonio Lozano:
A Review on Outlier/Anomaly Detection in Time Series Data. ACM Comput. Surv. 54(3): 56:1-56:33 (2022) - [j132]Jon Vadillo, Roberto Santana, José Antonio Lozano:
Analysis of dominant classes in universal adversarial perturbations. Knowl. Based Syst. 236: 107719 (2022) - [j131]Amaia Abanda, Usue Mori, José Antonio Lozano:
Ad-hoc explanation for time series classification. Knowl. Based Syst. 252: 109366 (2022) - [j130]Imanol Unanue, María Merino, José Antonio Lozano:
A mathematical analysis of EDAs with distance-based exponential models. Memetic Comput. 14(3): 305-334 (2022) - [j129]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) - [j128]Amaia Abanda, Usue Mori, José Antonio Lozano:
Time series classifier recommendation by a meta-learning approach. Pattern Recognit. 128: 108671 (2022) - [j127]Abolfazl Shirazi, Josu Ceberio, José Antonio Lozano:
EDA++: Estimation of Distribution Algorithms With Feasibility Conserving Mechanisms for Constrained Continuous Optimization. IEEE Trans. Evol. Comput. 26(5): 1144-1156 (2022) - [j126]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) - [j125]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) - [c99]Mario Martínez-García, Susana García-Gutierrez, Rubén Armañanzas, Adrián Díaz, Iñaki Inza, José Antonio Lozano:
Learning a Battery of COVID-19 Mortality Prediction Models by Multi-objective Optimization. AIME 2022: 332-342 - [c98]Jairo Rojas-Delgado, J. A. Jiménez, Rafael Bello, José Antonio Lozano:
Hyper-parameter Optimization Using Continuation Algorithms. MIC 2022: 365-377 - [c97]Anne Elorza, Leticia Hernando, José Antonio Lozano:
Transitions from P to NP-hardness: the case of the Linear Ordering Problem. CEC 2022: 1-8 - [c96]Verónica Álvarez, Santiago Mazuelas, José Antonio Lozano:
Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees. ICML 2022: 486-499 - [c95]Gia Sirbiladze, Janusz Kacprzyk, José Antonio Lozano, Bezhan Ghvaberidze, Bidzina Midodashvili, Bidzina Matsaberidze:
Fuzzy Approach for the Temporary Logistics Hubs' Selection Planning in Disaster Region. IS 2022: 1-5 - [c94]Gia Sirbiladze, Janusz Kacprzyk, José Antonio Lozano, Bezhan Ghvaberidze, Bidzina Midodashvili, Bidzina Matsaberidze:
Fuzzy Model of Humanitarian Relief Logistics for the Shelters' Location in the Disaster Region and Evacuation of Population. IS 2022: 1-5 - [c93]Gia Sirbiladze, Janusz Kacprzyk, José Antonio Lozano, Bezhan Ghvaberidze, Bidzina Midodashvili, Bidzina Matsaberidze:
Fuzzy Approach to Planning of Service Centers Location and Goods Transportation Routes in the Disaster Region. IS 2022: 1-5 - [i21]Anne Elorza, Leticia Hernando, José Antonio Lozano:
Transitions from P to NP-hardness: the case of the Linear Ordering Problem. CoRR abs/2205.12943 (2022) - [i20]Verónica Álvarez, Santiago Mazuelas, José Antonio Lozano:
Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees. CoRR abs/2205.15942 (2022) - [i19]Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto:
A Survey on Preserving Fairness Guarantees in Changing Environments. CoRR abs/2211.07530 (2022) - 2021
- [j124]Ibai Roman, Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Evolution of Gaussian Process kernels for machine translation post-editing effort estimation. Ann. Math. Artif. Intell. 89(8-9): 835-856 (2021) - [j123]Gorka Kobeaga, María Merino, José Antonio Lozano:
On solving cycle problems with Branch-and-Cut: extending shrinking and exact subcycle elimination separation algorithms. Ann. Oper. Res. 305(1): 107-136 (2021) - [j122]César Montenegro, Roberto Santana, José Antonio Lozano:
Analysis of the sensitivity of the End-Of-Turn Detection task to errors generated by the Automatic Speech Recognition process. Eng. Appl. Artif. Intell. 100: 104189 (2021) - [j121]Ibai Roman, Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Evolving Gaussian process kernels from elementary mathematical expressions for time series extrapolation. Neurocomputing 462: 426-439 (2021) - [j120]Ane Blázquez-García, Angel Conde, Usue Mori, José Antonio Lozano:
Water leak detection using self-supervised time series classification. Inf. Sci. 574: 528-541 (2021) - [j119]Ibai Roman, Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
In-depth analysis of SVM kernel learning and its components. Neural Comput. Appl. 33(12): 6575-6594 (2021) - [j118]Javier Moreno, Daniel Rodríguez, Antonio J. Nebro, José Antonio Lozano:
Merge Nondominated Sorting Algorithm for Many-Objective Optimization. IEEE Trans. Cybern. 51(12): 6154-6164 (2021) - [j117]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) - [c92]Imanol Unanue, María Merino, José Antonio Lozano:
A General Framework Based on Walsh Decomposition for Combinatorial Optimization Problems. CEC 2021: 391-398 - [c91]Javier Mikel Olaso, Alain Vázquez, Leila Ben Letaifa, Mikel de Velasco, Aymen Mtibaa, Mohamed Amine Hmani, Dijana Petrovska-Delacrétaz, Gérard Chollet, César Montenegro, Asier López-Zorrilla, Raquel Justo, Roberto Santana, Jofre Tenorio-Laranga, Eduardo González-Fraile, Begoña Fernández-Ruanova, Gennaro Cordasco, Anna Esposito, Kristin Beck Gjellesvik, Anna Torp Johansen, Maria Stylianou Korsnes, Colin Pickard, Cornelius Glackin, Gary Cahalane, Pau Buch-Cardona, Cristina Palmero, Sergio Escalera, Olga Gordeeva, Olivier Deroo, Anaïs Fernández, Daria Kyslitska, José Antonio Lozano, María Inés Torres, Stephan Schlögl:
The EMPATHIC Virtual Coach: a demo. ICMI 2021: 848-851 - [e10]Nuria Oliver, Fernando Pérez-Cruz, Stefan Kramer, Jesse Read, José Antonio Lozano:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part I. Lecture Notes in Computer Science 12975, Springer 2021, ISBN 978-3-030-86485-9 [contents] - [e9]Nuria Oliver, Fernando Pérez-Cruz, Stefan Kramer, Jesse Read, José Antonio Lozano:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part II. Lecture Notes in Computer Science 12976, Springer 2021, ISBN 978-3-030-86519-1 [contents] - [e8]Nuria Oliver, Fernando Pérez-Cruz, Stefan Kramer, Jesse Read, José Antonio Lozano:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part III. Lecture Notes in Computer Science 12977, Springer 2021, ISBN 978-3-030-86522-1 [contents] - [e7]Yuxiao Dong, Nicolas Kourtellis, Barbara Hammer, José Antonio Lozano:
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part IV. Lecture Notes in Computer Science 12978, Springer 2021, ISBN 978-3-030-86513-9 [contents] - [e6]Yuxiao Dong, Nicolas Kourtellis, Barbara Hammer, José Antonio Lozano:
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part V. Lecture Notes in Computer Science 12979, Springer 2021, ISBN 978-3-030-86516-0 [contents] - [i18]M. Inés Torres, Javier Mikel Olaso, César Montenegro, Roberto Santana, Alain Vázquez, Raquel Justo, José Antonio Lozano, Stephan Schlögl, Gérard Chollet, Nazim Dugan, M. Irvine, Neil Glackin, Colin Pickard, Anna Esposito, Gennaro Cordasco, Alda Troncone, Dijana Petrovska-Delacrétaz, Aymen Mtibaa, Mohamed Amine Hmani, Maria Stylianou Korsnes, L. J. Martinussen, Sergio Escalera, Cristina Palmero Cantariño, Olivier Deroo, Olga Gordeeva, Jofre Tenorio-Laranga, Eduardo Gonzalez-Fraile, Begonya Fernandez-Ruanova, A. Gonzalez-Pinto:
The EMPATHIC Project: Mid-term Achievements. CoRR abs/2105.01878 (2021) - [i17]Jon Vadillo, Roberto Santana, José Antonio Lozano:
When and How to Fool Explainable Models (and Humans) with Adversarial Examples. CoRR abs/2107.01943 (2021) - 2020
- [j116]Ander Carreño, Iñaki Inza, José Antonio Lozano:
Analyzing rare event, anomaly, novelty and outlier detection terms under the supervised classification framework. Artif. Intell. Rev. 53(5): 3575-3594 (2020) - [j115]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) - [j114]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) - [j113]Josu Ircio, Aizea Lojo, Usue Mori, José Antonio Lozano:
Mutual information based feature subset selection in multivariate time series classification. Pattern Recognit. 108: 107525 (2020) - [c90]Leticia Hernando, Alexander Mendiburu, José Antonio Lozano:
Journey to the center of the linear ordering problem. GECCO 2020: 201-209 - [c89]César Montenegro, Roberto Santana, José Antonio Lozano:
Transfer learning in hierarchical dialogue topic classification with neural networks*. IJCNN 2020: 1-8 - [c88]Jon Vadillo, Roberto Santana, José Antonio Lozano:
Exploring Gaps in DeepFool in Search of More Effective Adversarial Perturbations. LOD (2) 2020: 215-227 - [i16]Ane Blázquez-García, Angel Conde, Usue Mori, José Antonio Lozano:
A review on outlier/anomaly detection in time series data. CoRR abs/2002.04236 (2020) - [i15]Jon Vadillo, Roberto Santana, José Antonio Lozano:
Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions. CoRR abs/2004.06383 (2020) - [i14]Gorka Kobeaga, María Merino, José Antonio Lozano:
On Solving Cycle Problems with Branch-and-Cut: Extending Shrinking and Exact Subcycle Elimination Separation Algorithms. CoRR abs/2004.14574 (2020) - [i13]Gorka Kobeaga, María Merino, José Antonio Lozano:
A revisited branch-and-cut algorithm for large-scale orienteering problems. CoRR abs/2011.02743 (2020) - [i12]Verónica Álvarez, Santiago Mazuelas, José Antonio Lozano:
Probabilistic Load Forecasting Based on Adaptive Online Learning. CoRR abs/2011.14721 (2020) - [i11]Jon Vadillo, Roberto Santana, José Antonio Lozano:
Analysis of Dominant Classes in Universal Adversarial Perturbations. CoRR abs/2012.14352 (2020)
2010 – 2019
- 2019
- [j112]Ibai Roman, Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
An Experimental Study in Adaptive Kernel Selection for Bayesian Optimization. IEEE Access 7: 184294-184302 (2019) - [j111]Amaia Abanda, Usue Mori, José Antonio Lozano:
A review on distance based time series classification. Data Min. Knowl. Discov. 33(2): 378-412 (2019) - [j110]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) - [j109]Leticia Hernando, Alexander Mendiburu, José Antonio Lozano:
Anatomy of the Attraction Basins: Breaking with the Intuition. Evol. Comput. 27(3): 435-466 (2019) - [j108]Jerónimo Hernández-González, Iñaki Inza, Igor Granado, Oihane C. Basurko, Jose A. Fernandes, José Antonio Lozano:
Aggregated outputs by linear models: An application on marine litter beaching prediction. Inf. Sci. 481: 381-393 (2019) - [j107]Usue Mori, Alexander Mendiburu, Isabel Marta Miranda, José Antonio Lozano:
Early classification of time series using multi-objective optimization techniques. Inf. Sci. 492: 204-218 (2019) - [j106]Diana Carrera, Lourenço P. C. Bandeira, Roberto Santana, José Antonio Lozano:
Detection of sand dunes on Mars using a regular vine-based classification approach. Knowl. Based Syst. 163: 858-874 (2019) - [j105]César Montenegro, Asier López-Zorrilla, Javier Mikel Olaso, Roberto Santana, Raquel Justo, José Antonio Lozano, María Inés Torres:
A Dialogue-Act Taxonomy for a Virtual Coach Designed to Improve the Life of Elderly. Multimodal Technol. Interact. 3(3): 52 (2019) - [j104]José Antonio Lozano, Ke Tang, Xin Yao:
Preface. Nat. Comput. 18(2): 285-286 (2019) - [j103]Izaskun Oregi, Aritz Pérez, Javier Del Ser, José Antonio Lozano:
On-line Elastic Similarity Measures for time series. Pattern Recognit. 88: 506-517 (2019) - [j102]Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano:
A Note on the Behavior of Majority Voting in Multi-Class Domains with Biased Annotators. IEEE Trans. Knowl. Data Eng. 31(1): 195-200 (2019) - [c87]Erik Garcia, Josu Ceberio, José Antonio Lozano:
Hybrid Heuristics for the Linear Ordering Problem. CEC 2019: 1431-1438 - [c86]Leticia Hernando, Alexander Mendiburu, José Antonio Lozano:
Characterising the rankings produced by combinatorial optimisation problems and finding their intersections. GECCO 2019: 266-273 - [c85]Imanol Unanue, María Merino, José Antonio Lozano:
A mathematical analysis of EDAs with distance-based exponential models. GECCO (Companion) 2019: 429-430 - [c84]Ibai Roman, Alexander Mendiburu, Roberto Santana, José Antonio Lozano:
Sentiment analysis with genetically evolved gaussian kernels. GECCO 2019: 1328-1337 - [c83]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 - [c82]Ibai Roman, Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Evolving Gaussian Process Kernels for Translation Editing Effort Estimation. LION 2019: 304-318 - [c81]Ibai Roman, Alexander Mendiburu, Roberto Santana, José Antonio Lozano:
Bayesian Optimization Approaches for Massively Multi-modal Problems. LION 2019: 383-397 - [c80]César Montenegro, Roberto Santana, José Antonio Lozano:
Data generation approaches for topic classification in multilingual spoken dialog systems. PETRA 2019: 211-217 - [c79]María Inés Torres, Javier Mikel Olaso, César Montenegro, Roberto Santana, Alain Vázquez, Raquel Justo, José Antonio Lozano, Stephan Schlögl, Gérard Chollet, Nazim Dugan, M. Irvine, Neil Glackin, Colin Pickard, Anna Esposito, Gennaro Cordasco, Alda Troncone, Dijana Petrovska-Delacrétaz, Aymen Mtibaa, Mohamed Amine Hmani, Maria Stylianou Korsnes, L. J. Martinussen, Sergio Escalera, Cristina Palmero Cantariño, Olivier Deroo, Olga Gordeeva, Jofre Tenorio-Laranga, Eduardo Gonzalez-Fraile, Begoñya Fernández-Ruanova, A. Gonzalez-Pinto:
The EMPATHIC project: mid-term achievements. PETRA 2019: 629-638 - [i10]Ibai Roman, Alexander Mendiburu, Roberto Santana, José Antonio Lozano:
Sentiment analysis with genetically evolved Gaussian kernels. CoRR abs/1904.00977 (2019) - [i9]Anne Elorza, Leticia Hernando, José Antonio Lozano:
Taxonomization of Combinatorial Optimization Problems in Fourier Space. CoRR abs/1905.10852 (2019) - [i8]Ibai Roman, Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Evolving Gaussian Process kernels from elementary mathematical expressions. CoRR abs/1910.05173 (2019) - 2018
- [j101]Jerónimo Hernández-González, Daniel Rodríguez, Iñaki Inza, Rachel Harrison, José Antonio Lozano:
Learning to classify software defects from crowds: A novel approach. Appl. Soft Comput. 62: 579-591 (2018) - [j100]Gorka Kobeaga, María Merino, José Antonio Lozano:
An efficient evolutionary algorithm for the orienteering problem. Comput. Oper. Res. 90: 42-59 (2018) - [j99]Pablo Rozas Larraondo, Iñaki Inza, José Antonio Lozano:
A system for airport weather forecasting based on circular regression trees. Environ. Model. Softw. 100: 24-32 (2018) - [j98]Pedro Pinacho Davidson, Christian Blum, José Antonio Lozano:
The weighted independent domination problem: Integer linear programming models and metaheuristic approaches. Eur. J. Oper. Res. 265(3): 860-871 (2018) - [j97]Jose Antonio Pascual, José Antonio Lozano, José Miguel-Alonso:
Effects of Reducing VMs Management Times on Elastic Applications. J. Grid Comput. 16(3): 513-530 (2018) - [j96]Anne Elorza, Leticia Hernando, Alexander Mendiburu, José Antonio Lozano:
Estimating attraction basin sizes of combinatorial optimization problems. Prog. Artif. Intell. 7(4): 369-384 (2018) - [j95]Usue Mori, Alexander Mendiburu, Sanjoy Dasgupta, José Antonio Lozano:
Early Classification of Time Series by Simultaneously Optimizing the Accuracy and Earliness. IEEE Trans. Neural Networks Learn. Syst. 29(10): 4569-4578 (2018) - [c78]Josu Ceberio, Alexander Mendiburu, José Antonio Lozano:
Distance-Based Exponential Probability Models for Constrained Combinatorial Problems. CAEPIA 2018: 187-197 - [c77]Leticia Hernando, Alexander Mendiburu, José Antonio Lozano:
Hill-Climbing Algorithm: Let's Go for a Walk Before Finding the Optimum. CEC 2018: 1-7 - [c76]Aritz Pérez, Josu Ceberio, José Antonio Lozano:
Are the Artificially Generated Instances Uniform in Terms of Difficulty? CEC 2018: 1-8 - [c75]Josu Ceberio, Alexander Mendiburu, José Antonio Lozano:
Distance-based exponential probability models on constrained combinatorial optimization problems. GECCO (Companion) 2018: 137-138 - [c74]Borja Calvo, Josu Ceberio, José Antonio Lozano:
Bayesian inference for algorithm ranking analysis. GECCO (Companion) 2018: 324-325 - [c73]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 - [c72]Diana Carrera, Roberto Santana, José Antonio Lozano:
The Relationship Between Graphical Representations of Regular Vine Copulas and Polytrees. IPMU (3) 2018: 678-690 - [c71]Aritz Pérez, Christian Blum, José Antonio Lozano:
Approximating the maximum weighted decomposable graph problem with applications to probabilistic graphical models. PGM 2018: 320-331 - [r1]Rafael Martí, José Antonio Lozano, Alexander Mendiburu, Leticia Hernando:
Multi-start Methods. Handbook of Heuristics 2018: 155-175 - [i7]Marco Capó, Aritz Pérez, José Antonio Lozano:
An efficient K -means clustering algorithm for massive data. CoRR abs/1801.02949 (2018) - [i6]Amaia Abanda, Usue Mori, José Antonio Lozano:
A review on distance based time series classification. CoRR abs/1806.04509 (2018) - [i5]Javier Moreno, Daniel Rodríguez, Antonio J. Nebro, José Antonio Lozano:
Merge Non-Dominated Sorting Algorithm for Many-Objective Optimization. CoRR abs/1809.06106 (2018) - 2017
- [j94]José Antonio Lozano:
Conference Report on 2017 IEEE Congress on Evolutionary Computation (IEEE CEC 2017) [Conference Reports]. IEEE Comput. Intell. Mag. 12(4): 5-6 (2017) - [j93]Usue Mori, Alexander Mendiburu, Eamonn J. Keogh, José Antonio Lozano:
Reliable early classification of time series based on discriminating the classes over time. Data Min. Knowl. Discov. 31(1): 233-263 (2017) - [j92]Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano:
Learning from Proportions of Positive and Unlabeled Examples. Int. J. Intell. Syst. 32(2): 109-133 (2017) - [j91]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) - [j90]Olacir R. Castro Jr., Aurora T. R. Pozo, José Antonio Lozano, Roberto Santana:
Transfer weight functions for injecting problem information in the multi-objective CMA-ES. Memetic Comput. 9(2): 153-180 (2017) - [j89]Jonathan Ortigosa-Hernández, Iñaki Inza, José Antonio Lozano:
Measuring the class-imbalance extent of multi-class problems. Pattern Recognit. Lett. 98: 32-38 (2017) - [j88]Olacir R. Castro Jr., Aurora T. R. Pozo, José Antonio Lozano, Roberto Santana:
An investigation of clustering strategies in many-objective optimization: the I-Multi algorithm as a case study. Swarm Intell. 11(2): 101-130 (2017) - [j87]Haibo He, Robert Haas, Jun Fu, Barbara Hammer, Daniel W. C. Ho, Fakhri Karray, Dhireesha Kudithipudi, José Antonio Lozano, Teresa Bernarda Ludermir, Jacek Mandziuk, Stefano Melacci, Antonio Paiva, Hong Qiao, Alain Rakotomamonjy, Shiliang Sun, Johan A. K. Suykens, Meng Wang:
Editorial: A Successful Year and Looking Forward to 2017 and Beyond. IEEE Trans. Neural Networks Learn. Syst. 28(1): 2-7 (2017) - [c70]Olacir R. Castro Jr., Roberto Santana, José Antonio Lozano, Aurora T. R. Pozo:
Combining CMA-ES and MOEA/DD for many-objective optimization. CEC 2017: 1451-1458 - [c69]Josu Ceberio, Alexander Mendiburu, José Antonio Lozano:
A square lattice probability model for optimising the Graph Partitioning Problem. CEC 2017: 1629-1636 - [c68]Josu Ceberio, Alexander Mendiburu, José Antonio Lozano:
Are we generating instances uniformly at random? CEC 2017: 1645-1651 - [c67]José Antonio Lozano:
General chair's welcome. CEC 2017 - [c66]Abolfazl Shirazi, Josu Ceberio, José Antonio Lozano:
Evolutionary algorithms to optimize low-thrust trajectory design in spacecraft orbital precession mission. CEC 2017: 1779-1786 - [c65]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 - [c64]Pedro Pinacho Davidson, Christian Blum, José Antonio Lozano:
The Weighted Independent Domination Problem: ILP Model and Algorithmic Approaches. EvoCOP 2017: 201-214 - [c63]Roberto Santana, José Antonio Lozano:
Different scenarios for survival analysis of evolutionary algorithms. GECCO 2017: 825-832 - [c62]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
- [j86]Christian Blum, Pedro Pinacho Davidson, Manuel López-Ibáñez, José Antonio Lozano:
Construct, Merge, Solve & Adapt A new general algorithm for combinatorial optimization. Comput. Oper. Res. 68: 75-88 (2016) - [j85]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) - [j84]Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
A review of message passing algorithms in estimation of distribution algorithms. Nat. Comput. 15(1): 165-180 (2016) - [j83]Diana Carrera, Roberto Santana, José Antonio Lozano:
Vine copula classifiers for the mind reading problem. Prog. Artif. Intell. 5(4): 289-305 (2016) - [j82]Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano:
Weak supervision and other non-standard classification problems: A taxonomy. Pattern Recognit. Lett. 69: 49-55 (2016) - [j81]Usue Mori, Alexander Mendiburu, José Antonio Lozano:
Distance Measures for Time Series in R: The TSdist Package. R J. 8(2): 451 (2016) - [j80]Juan Wang, Ke Tang, José Antonio Lozano, Xin Yao:
Estimation of the Distribution Algorithm With a Stochastic Local Search for Uncertain Capacitated Arc Routing Problems. IEEE Trans. Evol. Comput. 20(1): 96-109 (2016) - [j79]Leticia Hernando, Alexander Mendiburu, José Antonio Lozano:
A Tunable Generator of Instances of Permutation-Based Combinatorial Optimization Problems. IEEE Trans. Evol. Comput. 20(2): 165-179 (2016) - [j78]Juanjuan Luo, Licheng Jiao, José Antonio Lozano:
A Sparse Spectral Clustering Framework via Multiobjective Evolutionary Algorithm. IEEE Trans. Evol. Comput. 20(3): 418-433 (2016) - [j77]Usue Mori, Alexander Mendiburu, José Antonio Lozano:
Similarity Measure Selection for Clustering Time Series Databases. IEEE Trans. Knowl. Data Eng. 28(1): 181-195 (2016) - [j76]Jonathan Ortigosa-Hernández, Iñaki Inza, José Antonio Lozano:
Semisupervised Multiclass Classification Problems With Scarcity of Labeled Data: A Theoretical Study. IEEE Trans. Neural Networks Learn. Syst. 27(12): 2602-2614 (2016) - [c61]Josu Ceberio, Alexander Mendiburu, José Antonio Lozano:
A Note on the Boltzmann Distribution and the Linear Ordering Problem. CAEPIA 2016: 441-446 - [c60]Leticia Hernando, Alexander Mendiburu, José Antonio Lozano:
Estimating Attraction Basin Sizes. CAEPIA 2016: 458-467 - [c59]Ibai Roman, Josu Ceberio, Alexander Mendiburu, José Antonio Lozano:
Bayesian optimization for parameter tuning in evolutionary algorithms. CEC 2016: 4839-4845 - [c58]Jose Antonio Pascual, José Antonio Lozano, José Miguel-Alonso:
Analyzing the Performance of Allocation Strategies Based on Space-Filling Curves. JSSPP 2016: 232-251 - [i4]Marco Capó, Aritz Pérez, José Antonio Lozano:
An efficient K-means algorithm for Massive Data. CoRR abs/1605.02989 (2016) - 2015
- [j75]Guzmán Santafé, Iñaki Inza, José Antonio Lozano:
Dealing with the evaluation of supervised classification algorithms. Artif. Intell. Rev. 44(4): 467-508 (2015) - [j74]Christian Blum, José Antonio Lozano, Pedro Pinacho Davidson:
An Artificial Bioindicator System for Network Intrusion Detection. Artif. Life 21(2): 93-118 (2015) - [j73]Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Multi-view classification of psychiatric conditions based on saccades. Appl. Soft Comput. 31: 308-316 (2015) - [j72]Josu Ceberio, Ekhine Irurozki, Alexander Mendiburu, José Antonio Lozano:
A review of distances for the Mallows and Generalized Mallows estimation of distribution algorithms. Comput. Optim. Appl. 62(2): 545-564 (2015) - [j71]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) - [j70]Josu Ceberio, Alexander Mendiburu, José Antonio Lozano:
The linear ordering problem revisited. Eur. J. Oper. Res. 241(3): 686-696 (2015) - [j69]Christian Blum, José Antonio Lozano, Pedro Pinacho Davidson:
Mathematical programming strategies for solving the minimum common string partition problem. Eur. J. Oper. Res. 242(3): 769-777 (2015) - [j68]Jose Antonio Pascual, Tania Lorido-Botran, José Miguel-Alonso, José Antonio Lozano:
Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies. J. Grid Comput. 13(3): 375-389 (2015) - [j67]Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano:
Multidimensional Learning from Crowds: Usefulness and Application of Expertise Detection. Int. J. Intell. Syst. 30(3): 326-354 (2015) - [j66]Zhanyong Wang, Jae Hoon Sul, Sagi Snir, José Antonio Lozano, Eleazar Eskin:
Gene-Gene Interactions Detection Using a Two-stage Model. J. Comput. Biol. 22(6): 563-576 (2015) - [j65]Carlos Echegoyen, Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Comprehensive characterization of the behaviors of estimation of distribution algorithms. Theor. Comput. Sci. 598: 64-86 (2015) - [j64]Xinle Liang, Huaping Chen, José Antonio Lozano:
A Boltzmann-Based Estimation of Distribution Algorithm for a General Resource Scheduling Model. IEEE Trans. Evol. Comput. 19(6): 793-806 (2015) - [j63]Jose Antonio Pascual, José Miguel-Alonso, José Antonio Lozano:
Locality-aware policies to improve job scheduling on 3D tori. J. Supercomput. 71(3): 966-994 (2015) - [j62]Peng Yang, Ke Tang, José Antonio Lozano, Xianbin Cao:
Path Planning for Single Unmanned Aerial Vehicle by Separately Evolving Waypoints. IEEE Trans. Robotics 31(5): 1130-1146 (2015) - [c57]Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano:
A Novel Weakly Supervised Problem: Learning from Positive-Unlabeled Proportions. CAEPIA 2015: 3-13 - [c56]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 - [c55]Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Evolving MNK-landscapes with structural constraints. CEC 2015: 1364-1371 - [c54]Josu Ceberio, Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Mixtures of Generalized Mallows models for solving the quadratic assignment problem. CEC 2015: 2050-2057 - [c53]Josu Ceberio, Alexander Mendiburu, José Antonio Lozano:
Kernels of Mallows Models for Solving Permutation-based Problems. GECCO 2015: 505-512 - [c52]Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Multi-objective NM-Landscapes. GECCO (Companion) 2015: 1477-1478 - [i3]Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Computing factorized approximations of Pareto-fronts using mNM-landscapes and Boltzmann distributions. CoRR abs/1512.03466 (2015) - 2014
- [j61]Jose Antonio Pascual, José Miguel-Alonso, José Antonio Lozano:
A fast implementation of the first fit contiguous partitioning strategy for cubic topologies. Concurr. Comput. Pract. Exp. 26(17): 2792-2810 (2014) - [j60]Tania Lorido-Botran, José Miguel-Alonso, José Antonio Lozano:
A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments. J. Grid Comput. 12(4): 559-592 (2014) - [j59]Ramón Sagarna, Alexander Mendiburu, Iñaki Inza, José Antonio Lozano:
Assisting in search heuristics selection through multidimensional supervised classification: A case study on software testing. Inf. Sci. 258: 122-139 (2014) - [j58]Jose Antonio Pascual, José Miguel-Alonso, José Antonio Lozano:
Application-aware metrics for partition selection in cube-shaped topologies. Parallel Comput. 40(5-6): 129-139 (2014) - [j57]Josu Ceberio, Ekhine Irurozki, Alexander Mendiburu, José Antonio Lozano:
A Distance-Based Ranking Model Estimation of Distribution Algorithm for the Flowshop Scheduling Problem. IEEE Trans. Evol. Comput. 18(2): 286-300 (2014) - [c51]Peng Yang, Ke Tang, José Antonio Lozano:
Estimation of Distribution Algorithms based Unmanned Aerial Vehicle path planner using a new coordinate system. IEEE Congress on Evolutionary Computation 2014: 1469-1476 - [c50]Josu Ceberio, Ekhine Irurozki, Alexander Mendiburu, José Antonio Lozano:
Extending distance-based ranking models in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation 2014: 2459-2466 - [c49]Tania Lorido-Botran, Jose Antonio Pascual, José Miguel-Alonso, José Antonio Lozano:
Optimization of Application Placement Towards a Greener Cloud Infrastructure. EvoApplications 2014: 690-701 - [c48]Christian Blum, José Antonio Lozano, Pedro Pinacho Davidson:
Iterative Probabilistic Tree Search for the Minimum Common String Partition Problem. Hybrid Metaheuristics 2014: 145-154 - [c47]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 - [c46]Zhanyong Wang, Jae Hoon Sul, Sagi Snir, José Antonio Lozano, Eleazar Eskin:
Gene-Gene Interactions Detection Using a Two-Stage Model. RECOMB 2014: 340-355 - [c45]Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Customized Selection in Estimation of Distribution Algorithms. SEAL 2014: 94-105 - [e5]Emilio Corchado, José Antonio Lozano, Héctor Quintián, Hujun Yin:
Intelligent Data Engineering and Automated Learning - IDEAL 2014 - 15th International Conference, Salamanca, Spain, September 10-12, 2014. Proceedings. Lecture Notes in Computer Science 8669, Springer 2014, ISBN 978-3-319-10839-1 [contents] - [i2]Christian Blum, José Antonio Lozano, Pedro Pinacho Davidson:
Mathematical Programming Strategies for Solving the Minimum Common String Partition Problem. CoRR abs/1405.5646 (2014) - 2013
- [j56]Carlos Echegoyen, Alexander Mendiburu, Roberto Santana, José Antonio Lozano:
On the Taxonomy of Optimization Problems Under Estimation of Distribution Algorithms. Evol. Comput. 21(3): 471-495 (2013) - [j55]Leticia Hernando, Alexander Mendiburu, José Antonio Lozano:
An Evaluation of Methods for Estimating the Number of Local Optima in Combinatorial Optimization Problems. Evol. Comput. 21(4): 625-658 (2013) - [j54]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) - [j53]Daniel P. Berrar, José Antonio Lozano:
Significance tests or confidence intervals: which are preferable for the comparison of classifiers? J. Exp. Theor. Artif. Intell. 25(2): 189-206 (2013) - [j52]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) - [j51]Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano:
Learning Bayesian network classifiers from label proportions. Pattern Recognit. 46(12): 3425-3440 (2013) - [c44]Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano:
Learning from Crowds in Multi-dimensional Classification Domains. CAEPIA 2013: 352-362 - [c43]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 - [c42]Josu Ceberio, Alexander Mendiburu, José Antonio Lozano:
The Plackett-Luce ranking model on permutation-based optimization problems. IEEE Congress on Evolutionary Computation 2013: 494-501 - [c41]Roberto Santana, Robert I. McKay, José Antonio Lozano:
Symmetry in evolutionary and estimation of distribution algorithms. IEEE Congress on Evolutionary Computation 2013: 2053-2060 - [c40]Josu Ceberio, Leticia Hernando, Alexander Mendiburu, José Antonio Lozano:
Understanding Instance Complexity in the Linear Ordering Problem. IDEAL 2013: 479-486 - [c39]Leticia Hernando, Alexander Mendiburu, José Antonio Lozano:
Generating Customized Landscapes in Permutation-Based Combinatorial Optimization Problems. LION 2013: 299-303 - [c38]Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Critical Issues in Model-Based Surrogate Functions in Estimation of Distribution Algorithms. SEMCCO (2) 2013: 1-13 - [c37]Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Message Passing Methods for Estimation of Distribution Algorithms Based on Markov Networks. SEMCCO (2) 2013: 419-430 - [i1]Pedro Larrañaga, Ramon Etxeberria, José Antonio Lozano, José M. Peña:
Combinatorial Optimization by Learning and Simulation of Bayesian Networks. CoRR abs/1301.3871 (2013) - 2012
- [j50]Izaskun Ibarbia, Alexander Mendiburu, Maria Santos, José Antonio Lozano:
An interactive optimization approach to a real-world oceanographic campaign planning problem. Appl. Intell. 36(3): 721-734 (2012) - [j49]Siddhartha Shakya, Roberto Santana, José Antonio Lozano:
A Markovianity based optimisation algorithm. Genet. Program. Evolvable Mach. 13(2): 159-195 (2012) - [j48]Jonathan Ortigosa-Hernández, Juan Diego Rodríguez, Leandro Alzate, Manuel Lucania, Iñaki Inza, José Antonio Lozano:
Approaching Sentiment Analysis by using semi-supervised learning of multi-dimensional classifiers. Neurocomputing 92: 98-115 (2012) - [j47]Borja Calvo, Iñaki Inza, Pedro Larrañaga, José Antonio Lozano:
Wrapper positive Bayesian network classifiers. Knowl. Inf. Syst. 33(3): 631-654 (2012) - [j46]Josu Ceberio, Ekhine Irurozki, Alexander Mendiburu, José Antonio Lozano:
A review on estimation of distribution algorithms in permutation-based combinatorial optimization problems. Prog. Artif. Intell. 1(1): 103-117 (2012) - [j45]Carlos Echegoyen, Alexander Mendiburu, Roberto Santana, José Antonio Lozano:
Toward Understanding EDAs Based on Bayesian Networks Through a Quantitative Analysis. IEEE Trans. Evol. Comput. 16(2): 173-189 (2012) - [j44]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) - [c36]Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Structural transfer using EDAs: An application to multi-marker tagging SNP selection. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c35]Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
An analysis of the use of probabilistic modeling for synaptic connectivity prediction from genomic data. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c34]Roberto Santana, Alexander Mendiburu, José Antonio Lozano:
Evolving NK-complexity for evolutionary solvers. GECCO (Companion) 2012: 1473-1474 - 2011
- [j43]Jose Antonio Pascual, José Miguel-Alonso, José Antonio Lozano:
Optimization-based mapping framework for parallel applications. J. Parallel Distributed Comput. 71(10): 1377-1387 (2011) - [j42]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) - [c33]Ekhine Irurozki, Borja Calvo, José Antonio Lozano:
Learning Probability Distributions over Permutations by Means of Fourier Coefficients. Canadian AI 2011: 186-191 - [c32]Carlos Echegoyen, Qingfu Zhang, Alexander Mendiburu, Roberto Santana, José Antonio Lozano:
On the limits of effectiveness in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation 2011: 1573-1580 - [c31]Leticia Hernando, Jose Antonio Pascual, Alexander Mendiburu, José Antonio Lozano:
A study on the complexity of TSP instances under the 2-exchange neighbor system. FOCI 2011: 15-21 - [c30]Josu Ceberio, Alexander Mendiburu, José Antonio Lozano:
A preliminary study on EDAs for permutation problems based on marginal-based models. GECCO 2011: 609-616 - [c29]Josu Ceberio, Alexander Mendiburu, José Antonio Lozano:
Introducing the Mallows Model on Estimation of Distribution Algorithms. ICONIP (2) 2011: 461-470 - [e4]José Antonio Lozano, José A. Gámez, José A. Moreno:
Advances in Artificial Intelligence - 14th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2011, La Laguna, Spain, November 7-11, 2011. Proceedings. Lecture Notes in Computer Science 7023, Springer 2011, ISBN 978-3-642-25273-0 [contents] - 2010
- [j41]Roberto Santana, Alexander Mendiburu, Noah Zaitlen, Eleazar Eskin, José Antonio Lozano:
Multi-marker tagging single nucleotide polymorphism selection using estimation of distribution algorithms. Artif. Intell. Medicine 50(3): 193-201 (2010) - [j40]Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
Learning Factorizations in Estimation of Distribution Algorithms Using Affinity Propagation. Evol. Comput. 18(4): 515-546 (2010) - [j39]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) - [c28]Carlos Echegoyen, Alexander Mendiburu, Roberto Santana, José Antonio Lozano:
Estimation of Bayesian networks algorithms in a class of complex networks. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c27]Jose Antonio Pascual, José Miguel-Alonso, José Antonio Lozano:
Strategies to Map Parallel Applications onto Meshes. DCAI 2010: 197-204 - [p10]Alexander Mendiburu, José Miguel-Alonso, José Antonio Lozano:
A Review on Parallel Estimation of Distribution Algorithms. Parallel and Distributed Computational Intelligence 2010: 143-163
2000 – 2009
- 2009
- [j38]Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
Research topics in discrete estimation of distribution algorithms based on factorizations. Memetic Comput. 1(1): 35-54 (2009) - [j37]Borja Calvo, Pedro Larrañaga, José Antonio Lozano:
Feature subset selection from positive and unlabelled examples. Pattern Recognit. Lett. 30(11): 1027-1036 (2009) - [j36]José Antonio Lozano, Qingfu Zhang, Pedro Larrañaga:
Guest Editorial: Special Issue on Evolutionary Algorithms Based on Probabilistic Models. IEEE Trans. Evol. Comput. 13(6): 1197-1198 (2009) - [c26]Ekhine Irurozki, José Antonio Lozano:
A new preprocessing procedure for the haplotype inference problem. IEEE Congress on Evolutionary Computation 2009: 1320-1327 - [c25]Carlos Echegoyen, Alexander Mendiburu, Roberto Santana, José Antonio Lozano:
Analyzing the probability of the optimum in EDAs based on Bayesian networks. IEEE Congress on Evolutionary Computation 2009: 1652-1659 - [c24]Roberto Santana, Concha Bielza, José Antonio Lozano, Pedro Larrañaga:
Mining probabilistic models learned by EDAs in the optimization of multi-objective problems. GECCO 2009: 445-452 - 2008
- [j35]Rubén Armañanzas, Iñaki Inza, Roberto Santana, Yvan Saeys, Jose Luis Flores, José Antonio Lozano, Yves Van de Peer, Rosa Blanco, Víctor Robles, Concha Bielza, Pedro Larrañaga:
A review of estimation of distribution algorithms in bioinformatics. BioData Min. 1 (2008) - [j34]Ramón Sagarna, José Antonio Lozano:
Dynamic Search Space Transformations for Software Test Data Generation. Comput. Intell. 24(1): 23-61 (2008) - [j33]Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
Combining variable neighborhood search and estimation of distribution algorithms in the protein side chain placement problem. J. Heuristics 14(5): 519-547 (2008) - [j32]Guzmán Santafé, José Antonio Lozano, Pedro Larrañaga:
Inference of Population Structure Using Genetic Markers and a Bayesian Model Averaging Approach for Clustering. J. Comput. Biol. 15(2): 207-220 (2008) - [j31]Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
Protein Folding in Simplified Models With Estimation of Distribution Algorithms. IEEE Trans. Evol. Comput. 12(4): 418-438 (2008) - [c23]Jayrani Cheeneebash, José Antonio Lozano, Harry C. S. Rughooputh:
A multi-objective approach to the Channel Assignment Problem. IEEE Congress on Evolutionary Computation 2008: 3913-3916 - [c22]Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
Component weighting functions for adaptive search with EDAs. IEEE Congress on Evolutionary Computation 2008: 4066-4073 - [c21]Juan Diego Rodríguez, José Antonio Lozano:
Multi-Objective Learning of Multi-Dimensional Bayesian Classifiers. HIS 2008: 501-506 - [c20]Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
Adding Probabilistic Dependencies to the Search of Protein Side Chain Configurations Using EDAs. PPSN 2008: 1120-1129 - [p9]Carlos Echegoyen, Roberto Santana, José Antonio Lozano, Pedro Larrañaga:
The Impact of Exact Probabilistic Learning Algorithms in EDAs Based on Bayesian Networks. Linkage in Evolutionary Computation 2008: 109-139 - [p8]Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
Adaptive Estimation of Distribution Algorithms. Adaptive and Multilevel Metaheuristics 2008: 177-197 - 2007
- [j30]Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
Side chain placement using estimation of distribution algorithms. Artif. Intell. Medicine 39(1): 49-63 (2007) - [j29]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) - [j28]Borja Calvo, Pedro Larrañaga, José Antonio Lozano:
Learning Bayesian classifiers from positive and unlabeled examples. Pattern Recognit. Lett. 28(16): 2375-2384 (2007) - [c19]Carlos Echegoyen, José Antonio Lozano, Roberto Santana, Pedro Larrañaga:
Exact Bayesian network learning in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation 2007: 1051-1058 - [c18]Guzmán Santafé, José Antonio Lozano, Pedro Larrañaga:
Discriminative vs. Generative Learning of Bayesian Network Classifiers. ECSQARU 2007: 453-464 - [c17]Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
The Role of a Priori Information in the Minimization of Contact Potentials by Means of Estimation of Distribution Algorithms. EvoBIO 2007: 247-257 - [c16]Alexander Mendiburu, Roberto Santana, José Antonio Lozano, Endika Bengoetxea:
A parallel framework for loopy belief propagation. GECCO (Companion) 2007: 2843-2850 - 2006
- [j27]Guzmán Santafé, José Antonio Lozano, Pedro Larrañaga:
Discriminative Learning of Bayesian Network Classifiers. Inteligencia Artif. 10(29): 39-47 (2006) - [j26]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) - [j25]Ramón Sagarna, José Antonio Lozano:
Scatter Search in software testing, comparison and collaboration with Estimation of Distribution Algorithms. Eur. J. Oper. Res. 169(2): 392-412 (2006) - [j24]Alexander Mendiburu, José Miguel-Alonso, José Antonio Lozano, Miren Ostra, Carlos Ubide:
Parallel EDAs to create multivariate calibration models for quantitative chemical applications. J. Parallel Distributed Comput. 66(8): 1002-1013 (2006) - [j23]Alexander Mendiburu, José Miguel-Alonso, José Antonio Lozano:
Implementation and Performance Evaluation of a Parallelization of Estimation of Bayesian Network Algorithms. Parallel Process. Lett. 16(1): 133-148 (2006) - [j22]Guzmán Santafé, José Antonio Lozano, Pedro Larrañaga:
Bayesian Model Averaging of Naive Bayes for Clustering. IEEE Trans. Syst. Man Cybern. Part B 36(5): 1149-1161 (2006) - [c15]Alexander Mendiburu, José Miguel-Alonso, José Antonio Lozano:
Evaluation of Parallel EDAs to Create Chemical Calibration Models. e-Science 2006: 118 - [c14]Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
Mixtures of Kikuchi Approximations. ECML 2006: 365-376 - [c13]Guzmán Santafé, José Antonio Lozano, Pedro Larrañaga:
Bayesian Model Averaging of TAN Models for Clustering. Probabilistic Graphical Models 2006: 271-278 - [e3]José Antonio Lozano, Pedro Larrañaga, Iñaki Inza, Endika Bengoetxea:
Towards a New Evolutionary Computation - Advances in the Estimation of Distribution Algorithms. Studies in Fuzziness and Soft Computing 192, Springer 2006, ISBN 978-3-540-29006-3 [contents] - 2005
- [j21]Ramón Sagarna, José Antonio Lozano:
On The Performance Of Estimation Of Distribution Algorithms Applied To Software Testing. Appl. Artif. Intell. 19(5): 457-489 (2005) - [j20]Pedro Larrañaga, José Antonio Lozano:
Editorial Introduction Special Issue on Estimation of Distribution Algorithms. Evol. Comput. 13(1) (2005) - [j19]José M. Peña, José Antonio Lozano, Pedro Larrañaga:
Globally Multimodal Problem Optimization Via an Estimation of Distribution Algorithm Based on Unsupervised Learning of Bayesian Networks. Evol. Comput. 13(1): 43-66 (2005) - [j18]Pedro Larrañaga, José Antonio Lozano, José M. Peña, Iñaki Inza:
Editorial. Mach. Learn. 59(3): 211-212 (2005) - [j17]Alexander Mendiburu, José Antonio Lozano, José Miguel-Alonso:
Parallel Implementation of EDAs Based on Probabilistic Graphical Models. IEEE Trans. Evol. Comput. 9(4): 406-423 (2005) - [c12]Rubén Armañanzas, José Antonio Lozano:
A multiobjective approach to the portfolio optimization problem. Congress on Evolutionary Computation 2005: 1388-1395 - [c11]Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
Interactions and dependencies in estimation of distribution algorithms. Congress on Evolutionary Computation 2005: 1418-1425 - [c10]Guzmán Santafé, José Antonio Lozano, Pedro Larrañaga:
Discriminative Learning of Bayesian Network Classifiers via the TM Algorithm. ECSQARU 2005: 148-160 - [c9]Alexander Mendiburu, José Miguel-Alonso, José Antonio Lozano, Miren Ostra, Carlos Ubide:
Parallel and Multi-Objective EDAs to Create Multivariate Calibration Models for Quantitative Chemical Applications. ICPP Workshops 2005: 596-603 - [c8]Cristina González, A. Ramírez, José Antonio Lozano, Pedro Larrañaga:
Average Time Complexity of Estimation of Distribution Algorithms. IWANN 2005: 42-49 - 2004
- [j16]José M. Peña, José Antonio Lozano, Pedro Larrañaga:
Unsupervised Learning Of Bayesian Networks Via Estimation Of Distribution Algorithms: An Application To Gene Expression Data Clustering. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 12(Supplement-1): 63-82 (2004) - [c7]Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
Protein Folding in 2-Dimensional Lattices with Estimation of Distribution Algorithms. ISBMDA 2004: 388-398 - [e2]Xin Yao, Edmund K. Burke, José Antonio Lozano, Jim Smith, Juan Julián Merelo Guervós, John A. Bullinaria, Jonathan E. Rowe, Peter Tiño, Ata Kabán, Hans-Paul Schwefel:
Parallel Problem Solving from Nature - PPSN VIII, 8th International Conference, Birmingham, UK, September 18-22, 2004, Proceedings. Lecture Notes in Computer Science 3242, Springer 2004, ISBN 3-540-23092-0 [contents] - 2003
- [j15]Pedro Larrañaga, José Antonio Lozano, Heinz Mühlenbein:
Algoritmos de Estimación de Distribuciones en Problemas de Optimización Combinatoria. Inteligencia Artif. 7(19): 149-168 (2003) - [c6]Cristina González, Juan Diego Rodríguez, José Antonio Lozano, Pedro Larrañaga:
Analysis of the Univariate Marginal Distribution Algorithm Modeled by Markov Chains. IWANN (1) 2003: 510-517 - 2002
- [j14]Pedro Larrañaga, José Antonio Lozano:
Synergies between evolutionary computation and probabilistic graphical models. Int. J. Approx. Reason. 31(3): 155-156 (2002) - [j13]Cristina González, José Antonio Lozano, Pedro Larrañaga:
Mathematical modelling of UMDAc algorithm with tournament selection. Behaviour on linear and quadratic functions. Int. J. Approx. Reason. 31(3): 313-340 (2002) - [j12]José M. Peña, José Antonio Lozano, Pedro Larrañaga:
Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction. Mach. Learn. 47(1): 63-89 (2002) - [c5]José M. Peña, José Antonio Lozano, Pedro Larrañaga:
Unsupervised Learning of Bayesian Networks Via Estimation of Distribution Algorithms. Probabilistic Graphical Models 2002 - [p7]José Antonio Lozano:
An Introduction to Evolutionary Algorithms. Estimation of Distribution Algorithms 2002: 3-25 - [p6]José M. Peña, José Antonio Lozano, Pedro Larrañaga:
Benefits of Data Clustering in Multimodal Function Optimization via EDAs. Estimation of Distribution Algorithms 2002: 101-127 - [p5]José Antonio Lozano, Ramón Sagarna, Pedro Larrañaga:
Parallel Estimation of Distribution Algorithms. Estimation of Distribution Algorithms 2002: 129-145 - [p4]Cristina González, José Antonio Lozano, Pedro Larrañaga:
Mathematical Modeling of Discrete Estimation of Distribution Algorithms. Estimation of Distribution Algorithms 2002: 147-163 - [p3]Rosa Blanco, José Antonio Lozano:
An Empirical Comparison of Discrete Estimation of Distribution Algorithms. Estimation of Distribution Algorithms 2002: 167-180 - [p2]Endika Bengoetxea, Teresa Miquélez, Pedro Larrañaga, José Antonio Lozano:
Experimental Results in Function Optimization with EDAs in Continuous Domain. Estimation of Distribution Algorithms 2002: 181-194 - [p1]José Antonio Lozano, Alexander Mendiburu:
Estimation of Distribution Algorithms Applied to the Job Shop Scheduling Problem: Some Preliminary Research. Estimation of Distribution Algorithms 2002: 231-242 - [e1]Pedro Larrañaga, José Antonio Lozano:
Estimation of Distribution Algorithms. Genetic Algorithms and Evolutionary Computation, Springer 2002, ISBN 978-1-4613-5604-2 [contents] - 2001
- [j11]José M. Peña, José Antonio Lozano, Pedro Larrañaga:
Performance evaluation of compromise conditional Gaussian networks for data clustering. Int. J. Approx. Reason. 28(1): 23-50 (2001) - [j10]José M. Peña, José Antonio Lozano, Pedro Larrañaga, Iñaki Inza:
Dimensionality Reduction in Unsupervised Learning of Conditional Gaussian Networks. IEEE Trans. Pattern Anal. Mach. Intell. 23(6): 590-603 (2001) - [c4]José M. Peña, I. Izarzugaza, José Antonio Lozano, E. Aldasoro, Pedro Larrañaga:
Geographical clustering of cancer incidence by means of Bayesian networks and conditional Gaussian networks. AISTATS 2001: 237-242 - 2000
- [j9]Cristina González, José Antonio Lozano, Pedro Larrañaga:
Analyzing the Population Based Incremental Learning Algorithm by Means of Discrete Dynamical Systems. Complex Syst. 12(4) (2000) - [j8]José M. Peña, José Antonio Lozano, Pedro Larrañaga:
An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering. Pattern Recognit. Lett. 21(8): 779-786 (2000) - [c3]Pedro Larrañaga, Ramon Etxeberria, José Antonio Lozano, José M. Peña:
Combinatonal Optimization by Learning and Simulation of Bayesian Networks. UAI 2000: 343-352
1990 – 1999
- 1999
- [j7]José Antonio Lozano, Pedro Larrañaga:
Applying genetic algorithms to search for the best hierarchical clustering of a dataset. Pattern Recognit. Lett. 20(9): 911-918 (1999) - [j6]José M. Peña, José Antonio Lozano, Pedro Larrañaga:
An empirical comparison of four initialization methods for the K-Means algorithm. Pattern Recognit. Lett. 20(10): 1027-1040 (1999) - [j5]Iñaki Inza, Pedro Larrañaga, Basilio Sierra, Ramon Etxeberria, José Antonio Lozano, José M. Peña:
Representing the behaviour of supervised classification learning algorithms by Bayesian networks. Pattern Recognit. Lett. 20(11-13): 1201-1209 (1999) - [j4]José M. Peña, José Antonio Lozano, Pedro Larrañaga:
Learning Bayesian networks for clustering by means of constructive induction. Pattern Recognit. Lett. 20(11-13): 1219-1230 (1999) - [j3]José Antonio Lozano, Pedro Larrañaga, Manuel Graña, F. Xabier Albizuri:
Genetic Algorithms: Bridging the Convergence Gap. Theor. Comput. Sci. 229(1): 11-22 (1999) - 1998
- [j2]José Antonio Lozano, Pedro Larrañaga:
Aplicación de los algoritmos genéticos al problema del clustering jerárquico. Inteligencia Artif. 2(5): 62-67 (1998) - 1997
- [c2]Ana Isabel González, Manuel Graña, José Antonio Lozano, Pedro Larrañaga:
Experimental Results of a Michigan-like Evolution Strategy for Non-stationary Clustering. ICANNGA 1997: 555-559 - 1996
- [j1]F. Xabier Albizuri, Alicia D'Anjou, Manuel Graña, José Antonio Lozano:
Convergence Properties of High-order Boltzmann Machines. Neural Networks 9(9): 1561-1567 (1996) - 1994
- [c1]Manuel Graña, Víctor Lavín Puente, Alicia D'Anjou, Francisco X. Albizuri, José Antonio Lozano:
High-order Boltzmann machines applied to the Monk's problems. ESANN 1994
Coauthor Index
aka: Aritz Pérez
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