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ORCIDJosé-Luis Sancho-Gómez
Publications
- 2022
[c25]María-Elena Fernández-García
, Antonio Ros-Ros, Eloy Hontoria Hernández, Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez:
Double-Layer Stacked Denoising Autoencoders for Regression. IWINAC (1) 2022: 337-345- 2021
- [j30]Adrián Sánchez-Morales, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
Complete autoencoders for classification with missing values. Neural Comput. Appl. 33(6): 1951-1957 (2021) - [j29]María-Elena Fernández-García, José-Luis Sancho-Gómez, Antonio Ros-Ros, Aníbal R. Figueiras-Vidal:
Complete Stacked Denoising Auto-Encoders for Regression. Neural Process. Lett. 53(1): 787-797 (2021) - 2020
- [j28]Juan-Antonio Martínez-García, José-Luis Sancho-Gómez, Adrián Sánchez-Morales, Aníbal R. Figueiras-Vidal:
Designing non-linear minimax and related discriminants by disjoint tangent configurations applied to RBF networks. Neurocomputing 383: 106-112 (2020) - [j27]Siham Tabik, Ricardo F. Alvear-Sandoval, María M. Ruiz, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Francisco Herrera:
MNIST-NET10: A heterogeneous deep networks fusion based on the degree of certainty to reach 0.1% error rate. Ensembles overview and proposal. Inf. Fusion 62: 73-80 (2020) - [j24]Adrián Sánchez-Morales, José-Luis Sancho-Gómez, Juan-Antonio Martínez-García, Aníbal R. Figueiras-Vidal:
Improving deep learning performance with missing values via deletion and compensation. Neural Comput. Appl. 32(17): 13233-13244 (2020) - [i1]Siham Tabik, Ricardo F. Alvear-Sandoval, María M. Ruiz, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Francisco Herrera:
A tutorial on ensembles and deep learning fusion with MNIST as guiding thread: A complex heterogeneous fusion scheme reaching 10 digits error. CoRR abs/2001.11486 (2020) - 2019
- [j23]Adrián Sánchez-Morales, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
Exploiting label information to improve auto-encoding based classifiers. Neurocomputing 370: 104-108 (2019) - [j22]Ricardo F. Alvear-Sandoval, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
On improving CNNs performance: The case of MNIST. Inf. Fusion 52: 106-109 (2019) - [c21]María-Elena Fernández-García, Jorge Larrey-Ruiz, Antonio Ros-Ros, Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez:
Machine-Health Application Based on Machine Learning Techniques for Prediction of Valve Wear in a Manufacturing Plant. IWINAC (2) 2019: 389-398 - 2018
- [j21]José-Luis Sancho-Gómez, Juan-Antonio Martínez-García, Stanley C. Ahalt, Aníbal R. Figueiras-Vidal:
Linear discriminants described by disjoint tangent configurations. Neurocomputing 316: 345-356 (2018) - 2017
- [c20]Adrián Sánchez-Morales, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
Values Deletion to Improve Deep Imputation Processes. IWINAC (2) 2017: 240-246 - 2013
- [j13]Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
Classifying patterns with missing values using Multi-Task Learning perceptrons. Expert Syst. Appl. 40(4): 1333-1341 (2013) - 2010
- [j7]Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
Pattern classification with missing data: a review. Neural Comput. Appl. 19(2): 263-282 (2010) - 2009
- [j6]José-Luis Sancho-Gómez, Pedro J. García-Laencina, Aníbal R. Figueiras-Vidal:
Combining Missing Data Imputation and Pattern Classification in a Multi-Layer Perceptron. Intell. Autom. Soft Comput. 15(4): 539-553 (2009) - [j5]Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Michel Verleysen:
K nearest neighbours with mutual information for simultaneous classification and missing data imputation. Neurocomputing 72(7-9): 1483-1493 (2009) - 2008
- [c8]Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Michel Verleysen:
K-nearest neighbours based on mutual information for incomplete data classification. ESANN 2008: 37-42 - 2007
- [c6]Pedro J. García-Laencina, Jesús Serrano-García, Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez:
Multi-task Neural Networks for Dealing with Missing Inputs. IWINAC (1) 2007: 282-291 - 2006
- [c4]Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
Pattern Classification with Missing Values using Multitask Learning. IJCNN 2006: 3594-3601 - 2005
- [c2]Pedro J. García-Laencina, Aníbal R. Figueiras-Vidal, Jesús Serrano-García, José-Luis Sancho-Gómez:
Exploiting Multitask Learning Schemes Using Private Subnetworks. IWANN 2005: 233-240 - 2000
- [j2]José-Luis Sancho, William E. Pierson, Batu Ulug, Aníbal R. Figueiras-Vidal, Stanley C. Ahalt:
Class separability estimation and incremental learning using boundary methods. Neurocomputing 35(1-4): 3-26 (2000) - [c1]Manel Martínez-Ramón, José-Luis Sancho-Gómez, Antonio Artés-Rodríguez, Aníbal R. Figueiras-Vidal:
Adaptive combination of LMS and logistic-linear equalizers to improve the speed-performance compromise. EUSIPCO 2000: 1-4 - 1999
- [j1]Abdelouahid Lyhyaoui, Manel Martínez-Ramón, Inma Mora, Maryan Vaquez, José-Luis Sancho, Aníbal R. Figueiras-Vidal:
Sample selection via clustering to construct support vector-like classifiers. IEEE Trans. Neural Networks 10(6): 1474-1481 (1999)
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