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2020 – today
- 2024
[j39]María Dolores Pérez-Godoy, Marta Molina, Francisco Martínez, David A. Elizondo, Francisco Charte, Antonio J. Rivera:
DESReg: Dynamic Ensemble Selection library for Regression tasks. Neurocomputing 580: 127487 (2024)- [j38]Bashar Alshouha
, Jesús Serrano-Guerrero, David A. Elizondo, Francisco P. Romero, José Angel Olivas:
What is the Consumer Attitude toward Healthcare Services? A Transfer Learning Approach for Detecting Emotions from Consumer Feedback. J. Univers. Comput. Sci. 30(1): 3-24 (2024) - [i8]Anthony Kenyon, Lipika Deka, David A. Elizondo:
Characterising Payload Entropy in Packet Flows. CoRR abs/2404.19121 (2024) - 2023
- [j37]Antonio Jesús Rivera, J. Cobo Muñoz, M. Dolores Pérez-Godoy, B. Sáenz de San Pedro, Francisco Charte, David A. Elizondo, C. Rodríguez, M. L. Abolafia, A. Perea, María José del Jesus:
XAIRE: An ensemble-based methodology for determining the relative importance of variables in regression tasks. Application to a hospital emergency department. Artif. Intell. Medicine 137: 102494 (2023) - [j36]Antonio J. Rivera, Miguel A. Dávila, David A. Elizondo, María José del Jesus, Francisco Charte:
mldr.resampling: Efficient reference implementations of multilabel resampling algorithms. Neurocomputing 559: 126806 (2023) - [j35]J. M. Górriz, I. Álvarez Illán, Agustín Álvarez Marquina, Juan Eloy Arco, Martin Atzmüller, F. Ballarini, Emilia I. Barakova, Guido Bologna, María Paula Bonomini, Germán Castellanos-Domínguez, Diego Castillo-Barnes, S. B. Cho, A. Ricardo Contreras, J. M. Cuadra, Enrique Domínguez, Francisco Domínguez-Mateos, Richard J. Duro, David A. Elizondo, Antonio Fernández-Caballero, Eduardo Fernández, Marco A. Formoso, Nicolás Gallego-Molina, Javier Gamazo, Javier González Jiménez, Jacob Rodriguez-Rivero, Carlos Garre del Olmo, F. Javier Garrigós, Andrés Gómez-Rodellar, Pedro Gómez Vilda, Manuel Graña, Bernabé Rodríguez-Tapia, Sophie C. F. Hendrikse, Carmen Jimenez-Mesa, Marina Jodra-Chuan, Vicente Julián, G. Gabriela Kotz, Krzysztof Kutt, Matthew Leming, Javier de Lope Asiaín, Beatriz del Cisne Macas Ordónez, V. Marrero-Aguiar, José Javier Martínez, Francisco Jesús Martínez-Murcia, Rafael Martínez-Tomás, Jirí Mekyska, Grzegorz J. Nalepa, Paulo Novais, D. Orellana, Andrés Ortiz, Daniel Palacios-Alonso, José T. Palma, António Pereira, Pedro Pinacho Davidson, María Angélica Pinninghoff, M. Ponticorvo, Alexandra Psarrou, Javier Ramírez, Mariano Rincón, V. Rodellar-Biarge, Ignacio Rodríguez-Rodríguez, Peter H. M. P. Roelofsma, José Santos, Diego Salas-Gonzalez, Pedro Salcedo Lagos, Fermín Segovia, Afshin Shoeibi, M. Silva, Dragan Simic, John Suckling, Jan Treur, Athanasios Tsanas, Ramiro Varela, S. H. Wang, Wei Wang, Y. D. Zhang, Hengde Zhu, Z. Zhu, J. M. Ferrández-Vicente:
Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends. Inf. Fusion 100: 101945 (2023) - [j34]Ricardo Javier Fuentes-Fino, Saúl Calderón Ramírez, Enrique Domínguez, Ezequiel López-Rubio, David A. Elizondo, Miguel A. Molina-Cabello:
An uncertainty estimator method based on the application of feature density to classify mammograms for breast cancer detection. Neural Comput. Appl. 35(30): 22151-22161 (2023) - [j33]Saúl Calderón Ramírez, Luis Oala, Jordina Torrents-Barrena, Shengxiang Yang, David A. Elizondo, Armaghan Moemeni, Simon Colreavy-Donnelly, Wojciech Samek, Miguel A. Molina-Cabello, Ezequiel López-Rubio:
Dataset Similarity to Assess Semisupervised Learning Under Distribution Mismatch Between the Labeled and Unlabeled Datasets. IEEE Trans. Artif. Intell. 4(2): 282-291 (2023) - [c34]Maria Isabel Cabrera-Bermejo, María José del Jesus, Antonio J. Rivera, David A. Elizondo, Francisco Charte, M. Dolores Pérez-Godoy:
Analysis of Transformer Model Applications. HAIS 2023: 231-243 - [i7]Antonio J. Rivera, Miguel A. Dávila, David A. Elizondo, María José del Jesus, Francisco Charte:
mldr.resampling: Efficient Reference Implementations of Multilabel Resampling Algorithms. CoRR abs/2305.17152 (2023) - [i6]Anthony Kenyon, David A. Elizondo, Lipika Deka:
Improved Flow Recovery from Packet Data. CoRR abs/2310.09834 (2023) - 2022
- [j32]Saúl Calderón Ramírez, Shengxiang Yang, David A. Elizondo, Armaghan Moemeni:
Dealing with distribution mismatch in semi-supervised deep learning for COVID-19 detection using chest X-ray images: A novel approach using feature densities. Appl. Soft Comput. 123: 108983 (2022) - [j31]Francisco J. Moreno-Barea, Leonardo Franco, David A. Elizondo, Martin Grootveld:
Application of data augmentation techniques towards metabolomics. Comput. Biol. Medicine 148: 105916 (2022) - [j30]Antonio J. Rivera, María Dolores Pérez-Godoy, David A. Elizondo, Lipika Deka, María José del Jesus:
Analysis of clustering methods for crop type mapping using satellite imagery. Neurocomputing 492: 91-106 (2022) - [j29]Saúl Calderón Ramírez, Diego Murillo-Hernandez, Kevin Rojas-Salazar, David A. Elizondo, Shengxiang Yang, Armaghan Moemeni, Miguel A. Molina-Cabello:
A real use case of semi-supervised learning for mammogram classification in a local clinic of Costa Rica. Medical Biol. Eng. Comput. 60(4): 1159-1175 (2022) - [j28]Saúl Calderón Ramírez, Shengxiang Yang, David A. Elizondo:
Semisupervised Deep Learning for Image Classification With Distribution Mismatch: A Survey. IEEE Trans. Artif. Intell. 3(6): 1015-1029 (2022) - [c33]Francisco J. Moreno-Barea, Leonardo Franco, David A. Elizondo, Martin Grootveld:
Data Augmentation Techniques to Improve Metabolomic Analysis in Niemann-Pick Type C Disease. ICCS (3) 2022: 78-91 - [i5]Saúl Calderón Ramírez, Shengxiang Yang, David A. Elizondo:
Semi-supervised Deep Learning for Image Classification with Distribution Mismatch: A Survey. CoRR abs/2203.00190 (2022) - 2021
- [j27]Noel Khan, David A. Elizondo, Lipika Deka, Miguel A. Molina-Cabello:
Fuzzy Logic Applied to System Monitors. IEEE Access 9: 56523-56538 (2021) - [j26]Saúl Calderón Ramírez, Shengxiang Yang, Armaghan Moemeni, Simon Colreavy-Donnelly, David A. Elizondo, Luis Oala, Jorge Rodríguez-Capitán, Manuel Jiménez-Navarro, Ezequiel López-Rubio, Miguel A. Molina-Cabello:
Improving Uncertainty Estimation With Semi-Supervised Deep Learning for COVID-19 Detection Using Chest X-Ray Images. IEEE Access 9: 85442-85454 (2021) - [j25]Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Enrique Domínguez, David A. Elizondo:
Skin Lesion Classification by Ensembles of Deep Convolutional Networks and Regularly Spaced Shifting. IEEE Access 9: 112193-112205 (2021) - [j24]Saúl Calderón Ramírez, Shengxiang Yang, Armaghan Moemeni, David A. Elizondo, Simon Colreavy-Donnelly, Luis Fernando Chavarria-Estrada, Miguel A. Molina-Cabello:
Correcting data imbalance for semi-supervised COVID-19 detection using X-ray chest images. Appl. Soft Comput. 111: 107692 (2021) - [j23]Juan Jesús Ruiz-Aguilar, Ignacio Turias, Javier González-Enrique, Daniel Urda, David A. Elizondo:
A permutation entropy-based EMD-ANN forecasting ensemble approach for wind speed prediction. Neural Comput. Appl. 33(7): 2369-2391 (2021) - [c32]Saúl Calderón Ramírez, Diego Murillo-Hernandez, Kevin Rojas-Salazar, Luis-Alexander Calvo-Valverde, Shengxiang Yang, Armaghan Moemeni, David A. Elizondo, Ezequiel López-Rubio, Miguel A. Molina-Cabello:
Improving Uncertainty Estimations for Mammogram Classification using Semi-Supervised Learning. IJCNN 2021: 1-8 - [c31]Willard Zamora-Cárdenas, Mauro Mendez, Saúl Calderón Ramírez, Martin Vargas, Gerardo Monge, Steve Quirós, David A. Elizondo, Jordina Torrents-Barrena, Miguel A. Molina-Cabello:
Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images. IWANN (1) 2021: 36-46 - [i4]Willard Zamora-Cárdenas, Mauro Mendez, Saúl Calderón Ramírez, Martin Vargas, Gerardo Monge, Steve Quirós, David A. Elizondo, Miguel A. Molina-Cabello:
Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images. CoRR abs/2106.05843 (2021) - [i3]Saúl Calderón Ramírez, Diego Murillo-Hernandez, Kevin Rojas-Salazar, David A. Elizondo, Shengxiang Yang, Miguel A. Molina-Cabello:
A Real Use Case of Semi-Supervised Learning for Mammogram Classification in a Local Clinic of Costa Rica. CoRR abs/2107.11696 (2021) - [i2]Saúl Calderón Ramírez, Shengxiang Yang, David A. Elizondo, Armaghan Moemeni:
Dealing with Distribution Mismatch in Semi-supervised Deep Learning for Covid-19 Detection Using Chest X-ray Images: A Novel Approach Using Feature Densities. CoRR abs/2109.00889 (2021) - 2020
- [j22]Miguel A. Molina-Cabello, David A. Elizondo, Rafael Marcos Luque Baena, Ezequiel López-Rubio:
Aggregation of Convolutional Neural Network Estimations of Homographies by Color Transformations of the Inputs. IEEE Access 8: 79552-79560 (2020) - [j21]Anthony Kenyon, Lipika Deka, David A. Elizondo:
Are public intrusion datasets fit for purpose characterising the state of the art in intrusion event datasets. Comput. Secur. 99: 102022 (2020) - [j20]Miguel A. Molina-Cabello, David A. Elizondo, Rafael M. Luque-Baena, Ezequiel López-Rubio:
Foreground detection by ensembles of random polygonal tilings. Expert Syst. Appl. 161: 113518 (2020) - [j19]Ángel Miguel García-Vico, Francisco Charte, Pedro González, David A. Elizondo, Cristóbal José Carmona:
E2PAMEA: A fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments. Neurocomputing 415: 60-73 (2020) - [c30]Saúl Calderón Ramírez, Raghvendra Giri, Shengxiang Yang, Armaghan Moemeni, Mario Umaña, David A. Elizondo, Jordina Torrents-Barrena, Miguel A. Molina-Cabello:
Dealing with Scarce Labelled Data: Semi-supervised Deep Learning with Mix Match for Covid-19 Detection Using Chest X-ray Images. ICPR 2020: 5294-5301 - [c29]Antonio Jesús Rivera, María Dolores Pérez-Godoy, David A. Elizondo, Lipika Deka, María José del Jesus:
A Preliminary Study on Crop Classification with Unsupervised Algorithms for Time Series on Images with Olive Trees and Cereal Crops. SOCO 2020: 276-285 - [i1]Saúl Calderón Ramírez, Shengxiang Yang, Armaghan Moemeni, David A. Elizondo, Simon Colreavy-Donnelly, Luis Fernando Chavarria-Estrada, Miguel A. Molina-Cabello:
Correcting Data Imbalance for Semi-Supervised Covid-19 Detection Using X-ray Chest Images. CoRR abs/2008.08496 (2020)
2010 – 2019
- 2019
- [c28]Oskar Wysocki, Lipika Deka, David A. Elizondo:
Heavy duty vehicle fuel consumption modeling using artificial neural networks. ICAC 2019: 1-6 - [c27]Oskar Wysocki, Lipika Deka, David A. Elizondo, Jacek Kropiwnicki, Jacek Czyzewicz:
Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks. IWANN (1) 2019: 794-805 - [c26]Miguel A. Molina-Cabello, Benjamin N. Passow, Enrique Domínguez, David A. Elizondo, Jolanta Obszynska:
Infering Air Quality from Traffic Data Using Transferable Neural Network Models. IWANN (1) 2019: 832-843 - 2017
- [j18]David A. Elizondo, Shang-Ming Zhou, Charalambos Chrysostomou:
Light source detection for digital images in noisy scenes: a neural network approach. Neural Comput. Appl. 28(5): 899-909 (2017) - [c25]Noel Khan, David A. Elizondo, Benjamin N. Passow, Pamela A. Hardaker:
Pose invariance through registration for hierarchical feature based pattern recognition systems. IJCNN 2017: 2902-2910 - 2016
- [c24]Frédéric Magoulès, Michel Piliougine, David A. Elizondo:
Support Vector Regression for Electricity Consumption Prediction in a Building in Japan. CSE/EUC/DCABES 2016: 189-196 - 2015
- [j17]Ezequiel López-Rubio, David A. Elizondo, Martin Grootveld, José M. Jerez, Rafael M. Luque-Baena:
Computational Intelligence Techniques in Medicine. Comput. Math. Methods Medicine 2015: 196976:1-196976:2 (2015) - [j16]Cristóbal J. Carmona, Victor Ruiz-Rodado, María José del Jesus, A. Weber, Martin Grootveld, Pedro González, David A. Elizondo:
A fuzzy genetic programming-based algorithm for subgroup discovery and the application to one problem of pathogenesis of acute sore throat conditions in humans. Inf. Sci. 298: 180-197 (2015) - [c23]Alexis Le Compte, David A. Elizondo, Tim Watson:
A renewed approach to serious games for cyber security. CyCon 2015: 203-216 - 2014
- [c22]Pamela A. Hardaker, Benjamin N. Passow, David A. Elizondo:
Multiple sensor outputs and computational intelligence towards estimating state and speed for control of lower limb prostheses. UKCI 2014: 1-8 - 2013
- [j15]Rafael M. Luque-Baena, David A. Elizondo, Ezequiel López-Rubio, Esteban J. Palomo, Tim Watson:
Assessment of geometric features for individual identification and verification in biometric hand systems. Expert Syst. Appl. 40(9): 3580-3594 (2013) - [j14]David A. Elizondo, Robert Morris, Tim Watson, Benjamin N. Passow:
Constructive Recursive Deterministic Perceptron Neural Networks with Genetic Algorithms. Int. J. Pattern Recognit. Artif. Intell. 27(6) (2013) - [j13]Derong Liu, Charles Anderson, Ahmad Taher Azar, Giorgio Battistelli, Eduardo Bayro-Corrochano, Cristiano Cervellera, David A. Elizondo, Maurizio Filippone, Giorgio Gnecco, Xiaolin Hu, Tingwen Huang, Weifeng Liu, Wenlian Lu, Ana Maria Madureira, Igor Skrjanc, Thomas Villmann, Q. M. Jonathan Wu, Shengli Xie, Dong Xu:
Editorial A Successful Change From TNN to TNNLS and a Very Successful Year. IEEE Trans. Neural Networks Learn. Syst. 24(1): 1-7 (2013) - [c21]Benjamin N. Passow, David A. Elizondo, Francisco Chiclana, Simon Witheridge, Eric Goodyer:
Adapting traffic simulation for traffic management: A neural network approach. ITSC 2013: 1402-1407 - [c20]Pamela A. Hardaker, Benjamin N. Passow, David A. Elizondo:
State detection from electromyographic signals towards the control of prosthetic limbs. UKCI 2013: 120-127 - 2012
- [j12]David A. Elizondo, Ralph Birkenhead, Matías Gámez, Noelia García Rubio, Esteban Alfaro Cortés:
Linear separability and classification complexity. Expert Syst. Appl. 39(9): 7796-7807 (2012) - [j11]Esteban J. Palomo, John North, David A. Elizondo, Rafael Marcos Luque, Tim Watson:
Application of growing hierarchical SOM for visualisation of network forensics traffic data. Neural Networks 32: 275-284 (2012) - [c19]Sylvain Contassot-Vivier, David A. Elizondo:
A Near Linear Algorithm for Testing Linear Separability in Two Dimensions. EANN 2012: 114-124 - [p10]David A. Elizondo, Agusti Solanas, Antoni Martínez-Ballesté:
Computational Intelligence for Privacy and Security: Introduction. Computational Intelligence for Privacy and Security 2012: 1-4 - [p9]Christian Bitter, John North, David A. Elizondo, Tim Watson:
An Introduction to the Use of Neural Networks for Network Intrusion Detection. Computational Intelligence for Privacy and Security 2012: 5-24 - [p8]Sulaiman Al Amro, David A. Elizondo, Agusti Solanas, Antoni Martínez-Ballesté:
Evolutionary Computation in Computer Security and Forensics: An Overview. Computational Intelligence for Privacy and Security 2012: 25-34 - [p7]Sulaiman Al Amro, Francisco Chiclana, David A. Elizondo:
Application of Fuzzy Logic in Computer Security and Forensics. Computational Intelligence for Privacy and Security 2012: 35-49 - [p6]Esteban J. Palomo, David A. Elizondo, Enrique Domínguez, Rafael Marcos Luque, Tim Watson:
SOM-Based Techniques towards Hierarchical Visualisation of Network Forensics Traffic Data. Computational Intelligence for Privacy and Security 2012: 75-95 - [p5]Rafael Marcos Luque, David A. Elizondo, Ezequiel López-Rubio, Esteban J. Palomo:
Feature Selection of Hand Biometrical Traits Based on Computational Intelligence Techniques. Computational Intelligence for Privacy and Security 2012: 159-180 - [p4]Bernd Carsten Stahl, Moira Carroll-Mayer, David A. Elizondo, Kutoma Wakunuma, Yingqin Zheng:
Intelligence Techniques in Computer Security and Forensics: At the Boundaries of Ethics and Law. Computational Intelligence for Privacy and Security 2012: 237-258 - [e2]David A. Elizondo, Agusti Solanas, Antoni Martínez-Ballesté:
Computational Intelligence for Privacy and Security. Studies in Computational Intelligence 394, Springer 2012, ISBN 978-3-642-25236-5 [contents] - 2011
- [j10]David A. Elizondo, Juan Miguel Ortiz-de-Lazcano-Lobato, Ralph Birkenhead:
Choice effect of linear separability testing methods on constructive neural network algorithms: An empirical study. Expert Syst. Appl. 38(3): 2330-2346 (2011) - [c18]Rafael Marcos Luque, David A. Elizondo, Ezequiel López-Rubio, Esteban J. Palomo:
GA-based feature selection approach in biometric hand systems. IJCNN 2011: 246-253 - [c17]Esteban J. Palomo, John North, David A. Elizondo, Rafael Marcos Luque, Tim Watson:
Visualisation of network forensics traffic data with a self-organising map for qualitative features. IJCNN 2011: 1740-1747 - 2010
- [j9]Christian Bitter, David A. Elizondo, Yingjie Yang:
Natural language processing: a prolog perspective. Artif. Intell. Rev. 33(1-2): 151-173 (2010) - [c16]Christian Bitter, David A. Elizondo, Tim Watson:
Application of artificial neural networks and related techniques to intrusion detection. IJCNN 2010: 1-8 - [c15]Andreas Huemer, Mario Gongora, David A. Elizondo:
A robust reinforcement based self constructing neural network. IJCNN 2010: 1-7 - [c14]Bernd Carsten Stahl, David A. Elizondo, Moira Carroll-Mayer, Yingqin Zheng, Kutoma Wakunuma:
Ethical and legal issues of the use of computational intelligence techniques in computer security and computer forensics. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [c13]David A. Elizondo, Ralph Birkenhead, Matías Gámez, Noelia García Rubio, Esteban Alfaro Cortés:
Estimation of classification complexity. IJCNN 2009: 764-770 - [p3]Maria do Carmo Nicoletti, João Roberto Bertini Jr., David A. Elizondo, Leonardo Franco, José M. Jerez:
Constructive Neural Network Algorithms for Feedforward Architectures Suitable for Classification Tasks. Constructive Neural Networks 2009: 1-23 - [p2]David A. Elizondo, Juan Miguel Ortiz-de-Lazcano-Lobato, Ralph Birkenhead:
Analysis and Testing of the m-Class RDP Neural Network. Constructive Neural Networks 2009: 171-192 - [p1]Andreas Huemer, David A. Elizondo, Mario Gongora:
A Constructive Neural Network for Evolving a Machine Controller in Real-Time. Constructive Neural Networks 2009: 225-242 - [e1]Leonardo Franco, David A. Elizondo, José M. Jerez:
Constructive Neural Networks. Studies in Computational Intelligence 258, Springer 2009, ISBN 978-3-642-04511-0 [contents] - 2008
- [j8]Esteban Alfaro Cortés, Noelia García Rubio, Matías Gámez, David A. Elizondo:
Bankruptcy forecasting: An empirical comparison of AdaBoost and neural networks. Decis. Support Syst. 45(1): 110-122 (2008) - [c12]David A. Elizondo, Juan Miguel Ortiz-de-Lazcano-Lobato, Ralph Birkenhead:
On the Generalization of the m-Class RDP Neural Network. ICANN (2) 2008: 734-743 - [c11]Andreas Huemer, David A. Elizondo, Mario Gongora:
A Reward-Value Based Constructive Method for the Autonomous Creation of Machine Controllers. ICANN (2) 2008: 773-782 - [c10]David A. Elizondo, Shang-Ming Zhou, Charalambos Chrysostomou:
Surface Reconstruction Techniques Using Neural Networks to Recover Noisy 3D Scenes. ICANN (1) 2008: 857-866 - [c9]Andreas Huemer, Mario Gongora, David A. Elizondo:
Self Constructing Neural Network Robot Controller based on On-line Task Performance Feedback. ICINCO-ICSO 2008: 326-333 - [c8]Andreas Huemer, Mario Gongora, David A. Elizondo:
Evolving a neural network using dyadic connections. IJCNN 2008: 1019-1025 - 2007
- [j7]David A. Elizondo, Ralph Birkenhead, Mario Gongora, Éric D. Taillard, Patrick Luyima:
Analysis and test of efficient methods for building recursive deterministic perceptron neural networks. Neural Networks 20(10): 1095-1108 (2007) - [j6]Marcos Faúndez-Zanuy, David A. Elizondo, Miguel Angel Ferrer-Ballester, Carlos Manuel Travieso-González:
Authentication of Individuals using Hand Geometry Biometrics: A Neural Network Approach. Neural Process. Lett. 26(3): 201-216 (2007) - [c7]David A. Elizondo, Juan Miguel Ortiz-de-Lazcano-Lobato, Ralph Birkenhead:
A Novel and Efficient Method for Testing Non Linear Separability. ICANN (1) 2007: 737-746 - 2006
- [j5]David A. Elizondo:
The linear separability problem: some testing methods. IEEE Trans. Neural Networks 17(2): 330-344 (2006) - [c6]David A. Elizondo, Ralph Birkenhead, Éric D. Taillard:
The Generalisation of the Recursive Deterministic Perceptron. IJCNN 2006: 1776-1783 - 2005
- [c5]David A. Elizondo, Mario Gongora:
Current Trends on Knowledge Extraction and Neural Networks. ICANN (2) 2005: 485-490 - [c4]Mario Gongora, Tim Watson, David A. Elizondo:
A Novel Method for Extracting Knowledge from Neural Networks with Evolving SQL Queries. ICANN (2) 2005: 497-502 - 2002
- [j4]Mohamed Tajine, David A. Elizondo:
New methods for testing linear separability. Neurocomputing 47(1-4): 161-188 (2002)
1990 – 1999
- 1998
- [j3]Mohamed Tajine, David A. Elizondo:
Growing Methods for Constructing Recursive Deterministic Perceptron Neural Networks and Knowledge Extraction. Artif. Intell. 102(2): 295-322 (1998) - [j2]Mohamed Tajine, David A. Elizondo:
The recursive deterministic perceptron neural network. Neural Networks 11(9): 1571-1588 (1998) - 1997
- [j1]David A. Elizondo, Emile Fiesler:
A Survey of Partially Connected Neural Networks. Int. J. Neural Syst. 8(5-6): 535-558 (1997) - [c3]Mohamed Tajine, David A. Elizondo, Emile Fiesler, Jerzy Korczak:
The class of linear separability method. ESANN 1997 - [c2]Mohamed Tajine, David A. Elizondo, Emile Fiesler, Jerzy Korczak:
Adapting the 2-class recursive deterministic perceptron neural network to m-classes. ICNN 1997: 1542-1546 - 1995
- [c1]David A. Elizondo, Emile Fiesler, Jerzy Korczak:
Non-ontogenic sparse neural networks. ICNN 1995: 290-295
Coauthor Index
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