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Salvador García

Salvador García

Award Badge
Computer Science
Spain
2025

D-Index & Metrics

Computer Science

D-Index
69
Citations
47055
World Ranking
1912
National Ranking
21

Research.com Recognitions

  • 2025 - Research.com Computer Science in Spain Leader Award
  • 2022 - Research.com Computer Science in Spain Leader Award

Overview

Salvador García is affiliated with the University of Granada in Spain and has a research focus predominantly in the field of Computer Science with a substantial number of publications. Their work spans various subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Electrical and Electronic Engineering, and Information Systems.

The scientist's research topics cover a range of technical subjects, highlighting key areas such as:

  • Imbalanced Data Classification Techniques
  • Advanced Clustering Algorithms Research
  • Machine Learning and Data Classification
  • Face and Expression Recognition
  • Text and Document Classification Technologies
  • Data Management and Algorithms
  • Electricity Theft Detection Techniques

Several recent papers exemplify the scope and focus of Salvador García's research contributions. Notable publications include:

  • "A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and opportunities" (2020, Information Fusion)
  • "A tutorial on distance metric learning: Mathematical foundations, algorithms, experimental analysis, prospects and challenges" (2020, Neurocomputing)
  • "Multi-modality approaches for medical support systems: A systematic review of the last decade" (2023, Information Fusion)
  • "How to design the fair experimental classifier evaluation" (2021, Applied Soft Computing)
  • "EpilepsyNet: Novel automated detection of epilepsy using transformer model with EEG signals from 121 patient population" (2023, Computers in Biology and Medicine)

Salvador García frequently publishes in a number of venues, including:

  • arXiv (Cornell University)
  • Information Fusion
  • Neurocomputing
  • Applied Soft Computing
  • Applied Intelligence

The scientist collaborates often with several peers in the field, such as:

  • Francisco Herrera
  • Germán González-Almagro
  • José-Ramón Cano
  • Juan Luis Suárez
  • Julián Luengo

Best Publications

  • Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI

    Alejandro Barredo Arrieta;Natalia Díaz-Rodríguez;Javier Del Ser;Javier Del Ser;Adrien Bennetot;Adrien Bennetot

  • A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms

    Joaquín Derrac;Salvador García;Daniel Molina;Francisco Herrera

  • KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework

    J. Alcalá-Fdez;A. Fernández;J. Luengo;J. Derrac

  • Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power

    Salvador García;Alberto Fernández;Julián Luengo;Francisco Herrera

  • SMOTE for learning from imbalanced data: progress and challenges, marking the 15-year anniversary

    Alberto Fernández;Salvador García;Francisco Herrera;Nitesh V. Chawla

  • A study on the use of non-parametric tests for analyzing the evolutionary algorithms' behaviour: a case study on the CEC'2005 Special Session on Real Parameter Optimization

    Salvador García;Daniel Molina;Manuel Lozano;Francisco Herrera

  • An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics

    Victoria López;Alberto Fernández;Salvador García;Vasile Palade

  • KEEL: a software tool to assess evolutionary algorithms for data mining problems

    J. Alcalá-Fdez;L. Sánchez;S. García;M. J. del Jesus

  • An Extension on "Statistical Comparisons of Classifiers over Multiple Data Sets" for all Pairwise Comparisons

    Salvador García;Francisco Herrera

  • Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study

    Salvador Garcia;Joaquin Derrac;Jose Ramon Cano;Francisco Herrera

  • A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability

    S. García;A. Fernández;J. Luengo;F. Herrera

  • Recent Trends in the Use of Statistical Tests for Comparing Swarm and Evolutionary Computing Algorithms: Practical Guidelines and a Critical Review

    Jacinto Carrasco;Salvador García;María del Mar Rueda;S. Das

  • Big data preprocessing: methods and prospects

    Salvador García;Sergio Ramírez-Gallego;Julián Luengo;José Manuel Benítez

  • A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning

    Salvador Garcia;J. Luengo;José Antonio Sáez;Victoria López

  • Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study

    Isaac Triguero;Salvador García;Francisco Herrera

  • A survey on data preprocessing for data stream mining

    Sergio Ramrez-Gallego;Bartosz Krawczyk;Salvador Garca;Micha Woniak

  • A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and opportunities

    Sergio González;Salvador García;Javier Del Ser;Lior Rokach

  • Evolutionary undersampling for classification with imbalanced datasets: Proposals and taxonomy

    Salvador García;Francisco Herrera

  • A practical tutorial on autoencoders for nonlinear feature fusion: taxonomy, models, software and guidelines

    David Charte;Francisco Charte;Salvador García;María José del Jesus

  • A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets

    Alberto Fernández;Salvador García;María José del Jesus;Francisco Herrera

  • A Taxonomy and Experimental Study on Prototype Generation for Nearest Neighbor Classification

    I. Triguero;J. Derrac;S. Garcia;F. Herrera

Frequent Co-Authors

Francisco Herrera
Francisco Herrera University of Granada
Julián Luengo
Julián Luengo University of Granada
Isaac Triguero
Isaac Triguero University of Nottingham
Alberto Fernández
Alberto Fernández University of Granada
José Manuel Benítez
José Manuel Benítez University of Granada
Bartosz Krawczyk
Bartosz Krawczyk Rochester Institute of Technology
María José del Jesus
María José del Jesus University of Jaén
Javier Del Ser
Javier Del Ser University of the Basque Country
Pedro Antonio Gutiérrez
Pedro Antonio Gutiérrez University of Córdoba
Chris Cornelis
Chris Cornelis Ghent University

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