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Javier Pérez-Rodríguez
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2020 – today
- 2023
- [j17]Javier Pérez-Rodríguez
, Francisco Fernández-Navarro
Estimating ensemble weights for bagging regressors based on the mean-variance portfolio framework. Expert Syst. Appl. 229(Part A): 120462 (2023) - [c13]Ondrej Benedikt, Javier Pérez-Rodríguez, Patrick Meumeu Yomsi
Reducing Peak Temperature by Redistributing Idle-Time in Modern MPSoCs. ISORC 2023: 76-85 - [c12]Javier Pérez-Rodríguez
B-TSP: An Advanced Power Safe Management Strategy for modern Multi-core Platforms under Thermal-Aware Design. RTNS 2023: 34-44 - 2022
- [j16]José Antonio Barbero-Aparicio
Nonlinear physics opens a new paradigm for accurate transcription start site prediction. BMC Bioinform. 23(1): 565 (2022) - [j15]Carlos Perales-González
Global Negative Correlation Learning: A Unified Framework for Global Optimization of Ensemble Models. IEEE Trans. Neural Networks Learn. Syst. 33(8): 4031-4042 (2022) - [c11]Javier Pérez-Rodríguez, Patrick Meumeu Yomsi
A Thermal-Aware Approach for DVFS-enabled Multi-core Architectures. HPCC/DSS/SmartCity/DependSys 2022: 1904-1911 - 2021
- [j14]Carlos Perales-González
Negative Correlation Hidden Layer for the Extreme Learning Machine. Appl. Soft Comput. 109: 107482 (2021) - [j13]Javier Pérez-Rodríguez
Floating Search Methodology for Combining Classification Models for Site Recognition in DNA Sequences. IEEE ACM Trans. Comput. Biol. Bioinform. 18(6): 2471-2482 (2021) - [c10]Javier Pérez-Rodríguez, Patrick Meumeu Yomsi:
An Efficient Proactive Thermal-Aware Scheduler for DVFS-enabled Single-Core Processors. RTNS 2021: 144-154 - 2020
- [j12]Carlos Perales-González
Negative correlation learning in the extreme learning machine framework. Neural Comput. Appl. 32(17): 13805-13823 (2020) - [c9]Javier Pérez-Rodríguez, Patrick Meumeu Yomsi:
Work-in-Progress: Towards a fine-grain thermal model for uniform multi-core processors. RTSS 2020: 403-406
2010 – 2019
- 2019
- [j11]Carlos Perales-González
Regularized ensemble neural networks models in the Extreme Learning Machine framework. Neurocomputing 361: 196-211 (2019) - [c8]Javier Pérez-Rodríguez
Thermal-Aware Schedulability Analysis for Fixed-Priority Non-preemptive Real-Time Systems. RTSS 2019: 154-166 - 2018
- [j10]Javier Pérez-Rodríguez
A general framework for boosting feature subset selection algorithms. Inf. Fusion 44: 147-175 (2018) - [j9]Aida de Haro-García
Combining three strategies for evolutionary instance selection for instance-based learning. Swarm Evol. Comput. 42: 160-172 (2018) - 2016
- [j8]Javier Pérez-Rodríguez
Stepwise approach for combining many sources of evidence for site-recognition in genomic sequences. BMC Bioinform. 17: 117 (2016) - 2015
- [j7]Javier Pérez-Rodríguez
Simultaneous instance and feature selection and weighting using evolutionary computation: Proposal and study. Appl. Soft Comput. 37: 416-443 (2015) - 2014
- [j6]Javier Pérez-Rodríguez
Improving translation initiation site and stop codon recognition by using more than two classes. Bioinform. 30(19): 2702-2708 (2014) - [j5]Nicolás García-Pedrajas, Aida de Haro-García
A Scalable Memetic Algorithm for Simultaneous Instance and Feature Selection. Evol. Comput. 22(1): 1-45 (2014) - 2013
- [j4]Nicolás García-Pedrajas, Aida de Haro-García
A scalable approach to simultaneous evolutionary instance and feature selection. Inf. Sci. 228: 150-174 (2013) - [j3]Nicolás García-Pedrajas, Javier Pérez-Rodríguez
OligoIS: Scalable Instance Selection for Class-Imbalanced Data Sets. IEEE Trans. Cybern. 43(1): 332-346 (2013) - [c7]Javier Pérez-Rodríguez, Alexis G. Arroyo-Peña, Javier Martinez Luna:
A multiobjective approach for gene structure prediction. IWBBIO 2013: 437-447 - 2012
- [j2]Nicolás García-Pedrajas, Javier Pérez-Rodríguez
Multi-selection of instances: A straightforward way to improve evolutionary instance selection. Appl. Soft Comput. 12(11): 3590-3602 (2012) - [j1]Nicolás García-Pedrajas, Javier Pérez-Rodríguez
Class imbalance methods for translation initiation site recognition in DNA sequences. Knowl. Based Syst. 25(1): 22-34 (2012) - [c6]Javier Pérez-Rodríguez
A Comparative Study of Content Statistics of Coding Regions in an Evolutionary Computation Framework for Gene Prediction. IEA/AIE 2012: 206-215 - [p1]Aida de Haro-García, Javier Pérez-Rodríguez, Nicolás García-Pedrajas:
A Scalable Feature Selection Method to Improve the Analysis of Microarrays. Modern Advances in Intelligent Systems and Tools 2012: 87-92 - 2011
- [c5]Aida de Haro-García
A Comparison of Two Strategies for Scaling Up Instance Selection in Huge Datasets. CAEPIA 2011: 64-73 - [c4]Javier Pérez-Rodríguez
Instance Selection for Class Imbalanced Problems by Means of Selecting Instances More than Once. CAEPIA 2011: 104-113 - [c3]Aida de Haro-García
Feature Selection for Translation Initiation Site Recognition. IEA/AIE (2) 2011: 357-366 - [c2]Javier Pérez-Rodríguez
An Evolutionary Algorithm for Gene Structure Prediction. IEA/AIE (2) 2011: 386-395 - [c1]Javier Pérez-Rodríguez
Evolutionary computation, combined with support vector machines, for gene structure prediction. ISDA 2011: 1359-1364
Coauthor Index
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