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ORCIDMarcelino Lázaro
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2020 – today
- 2024
[j21]Javier Mediavilla-Relaño
, Marcelino Lázaro:
COCOA: Cost-Optimized COunterfactuAl explanation method. Inf. Sci. 670: 120616 (2024)- [j20]Javier Mediavilla-Relaño, Marcelino Lázaro:
One-step Bayesian example-dependent cost classification: The OsC-MLP method. Neural Networks 173: 106168 (2024) - 2023
- [j19]Javier Mediavilla-Relaño, Marcelino Lázaro, Aníbal R. Figueiras-Vidal:
Imbalance example-dependent cost classification: A Bayesian based method. Expert Syst. Appl. 213(Part): 118909 (2023) - [j18]Marcelino Lázaro, Aníbal R. Figueiras-Vidal:
Neural network for ordinal classification of imbalanced data by minimizing a Bayesian cost. Pattern Recognit. 137: 109303 (2023) - 2021
- [j17]Marcelino Lázaro, Aníbal R. Figueiras-Vidal:
A Bayes Risk Minimization Machine for Example-Dependent Cost Classification. IEEE Trans. Cybern. 51(7): 3524-3534 (2021) - 2020
- [j16]Marcelino Lázaro, Francisco Herrera, Aníbal R. Figueiras-Vidal:
Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification. Inf. Sci. 520: 31-45 (2020)
2010 – 2019
- 2019
- [c18]Javier Mediavilla-Relaño, Aitor Gutiérrez-López, Marcelino Lázaro, Aníbal R. Figueiras-Vidal:
A Principled Two-Step Method for Example-Dependent Cost Binary Classification. IWINAC (2) 2019: 13-22 - 2018
- [j15]Marcelino Lázaro, Monson H. Hayes, Aníbal R. Figueiras-Vidal:
Training neural network classifiers through Bayes risk minimization applying unidimensional Parzen windows. Pattern Recognit. 77: 204-215 (2018) - 2017
- [j14]Sergio González, Salvador García, Marcelino Lázaro, Aníbal R. Figueiras-Vidal, Francisco Herrera:
Class Switching according to Nearest Enemy Distance for learning from highly imbalanced data-sets. Pattern Recognit. 70: 12-24 (2017) - 2016
- [j13]Marcelino Lázaro:
Decentralized detection for censored binary observations with statistical dependence. Signal Process. 123: 112-121 (2016) - 2015
- [c17]Marcelino Lázaro, Francisco Herrera, Aníbal R. Figueiras-Vidal:
Classification of Binary Imbalanced Data Using A Bayesian Ensemble of Bayesian Neural Networks. EANN 2015: 304-314 - 2011
- [j12]Jorge Plata-Chaves, Marcelino Lázaro:
Closed-Form Error Exponent for the Neyman-Pearson Fusion of Dependent Local Decisions in a One-Dimensional Sensor Network. IEEE Trans. Signal Process. 59(3): 1239-1254 (2011) - [c16]Jorge Plata-Chaves, Marcelino Lázaro, Antonio Artés-Rodríguez:
Optimal Neyman-Pearson fusion in two-dimensional sensor networks with serial architecture and dependent observations. FUSION 2011: 1-6 - 2010
- [c15]Jorge Plata-Chaves, Marcelino Lázaro:
Closed-form error exponent for the Neyman-Pearson fusion of two-dimensional Markov local decisions. EUSIPCO 2010: 164-166
2000 – 2009
- 2009
- [j11]Marcelino Lázaro, Jonathan González-Olasola:
Blind equalization using the IRWLS formulation of the support vector machine. Signal Process. 89(7): 1436-1445 (2009) - [j10]Marcelino Lázaro, Matilde Sánchez Fernández, Antonio Artés-Rodríguez:
Optimal Sensor Selection in Binary Heterogeneous Sensor Networks. IEEE Trans. Signal Process. 57(4): 1577-1587 (2009) - 2007
- [c14]Juan C. Alonso-Bayal, Ricardo Santiago-Mozos, José M. Leiva-Murillo, Marcelino Lázaro, Antonio Artés-Rodríguez:
Real-time tracking and identification on an intelligent IR-based surveillance system. AVSS 2007: 277-282 - [c13]Marcelino Lázaro, Antonio Artés-Rodríguez:
Optimal Sensor Selection in Heterogeneous Sensor Networks. ICASSP (2) 2007: 1017-1020 - [c12]Marcelino Lázaro, José M. Leiva-Murillo, Antonio Artés-Rodríguez, Aníbal R. Figueiras-Vidal:
A New Cost Function for Binary Classification Problems Based on the Distributions of the Soft Output for Each Class. IJCNN 2007: 1464-1469 - 2005
- [j9]Marcelino Lázaro, Ignacio Santamaría, Fernando Pérez-Cruz, Antonio Artés-Rodríguez:
Support Vector Regression for the simultaneous learning of a multivariate function and its derivatives. Neurocomputing 69(1-3): 42-61 (2005) - [j8]Marcelino Lázaro, Fernando Pérez-Cruz, Antonio Artés-Rodríguez:
Learning a function and its derivative forcing the support vector expansion. IEEE Signal Process. Lett. 12(3): 194-197 (2005) - [j7]Marcelino Lázaro, Ignacio Santamaría, Deniz Erdogmus, Kenneth E. Hild II, Carlos Pantaleón, José C. Príncipe:
Stochastic blind equalization based on PDF fitting using Parzen estimator. IEEE Trans. Signal Process. 53(2-1): 696-704 (2005) - [c11]Antonio Artés-Rodríguez, Marcelino Lázaro, Matilde Sánchez Fernández:
Decentralized detection in dense sensor networks with censored transmissions. ICASSP (4) 2005: 817-820 - 2004
- [j6]Deniz Erdogmus, Kenneth E. Hild II, José C. Príncipe, Marcelino Lázaro, Ignacio Santamaría:
Adaptive blind deconvolution of linear channels using Renyi's entropy with Parzen window estimation. IEEE Trans. Signal Process. 52(6): 1489-1498 (2004) - [c10]Marcelino Lázaro, Ignacio Santamaría, Javier Vía, Deniz Erdogmus:
Blind equalization of multilevel signals using support vector machines. EUSIPCO 2004: 41-44 - [c9]Javier Vía, Ignacio Santamaría, Marcelino Lázaro:
Blind restoration of binary signals using a line spectrum fitting approach. EUSIPCO 2004: 461-464 - [c8]Fernando Pérez-Cruz, Marcelino Lázaro, Antonio Artés-Rodríguez:
Multidimensional SVM to include the samples of the derivatives in the reconstruction of a function. EUSIPCO 2004: 597-600 - 2003
- [j5]Ignacio Santamaría, Jesús Ibáñez, Marcelino Lázaro, Carlos Pantaleón, Luis Vielva:
Modeling Nonlinear Power Amplifiers in OFDM Systems from Subsampled Data: A Comparative Study Using Real Measurements. EURASIP J. Adv. Signal Process. 2003(12): 1219-1228 (2003) - [j4]Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón:
A new EM-based training algorithm for RBF networks. Neural Networks 16(1): 69-77 (2003) - [j3]Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón, Jesús Ibáñez, Luis Vielva:
A regularized technique for the simultaneous reconstruction of a function and its derivatives with application to nonlinear transistor modeling. Signal Process. 83(9): 1859-1870 (2003) - [c7]Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón, Deniz Erdogmus, José C. Príncipe:
Matched pdf-based blind equalization. ICASSP (4) 2003: 297-300 - [c6]Marcelino Lázaro, Ignacio Santamaría, Fernando Pérez-Cruz, Antonio Artés-Rodríguez:
Support vector machine for the simultaneous approximation of a function and its derivative. NNSP 2003: 189-198 - 2001
- [j2]Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón:
Neural networks for large- and small-signal modeling of MESFET/HEMT transistors. IEEE Trans. Instrum. Meas. 50(6): 1587-1593 (2001) - [c5]Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón:
A regularized digital filtering technique for the simultaneous reconstruction of a function and its derivatives. ICECS 2001: 67-70 - [c4]Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón:
Accelerating the Convergence of EM-Based Training Algorithms for RBF Networks. IWANN (1) 2001: 347-354 - 2000
- [c3]Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón, Cesar Navarro, Antonio Tazón, Tomás Fernández Ibáñez:
A Modular Neural Network for Global Modeling of Microwave Transistors. IJCNN (4) 2000: 389-394 - [c2]Angel Mediavilla, Antonio Tazón, J. A. Pereda, Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón:
Neuronal Architecture for Waveguide Inductive Iris Bandpass Filter Optimization. IJCNN (4) 2000: 395-402 - [c1]Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón:
A smooth and derivable large-signal model for microwave HEMT transistors. ISCAS 2000: 713-716
1990 – 1999
- 1999
- [j1]Ignacio Santamaría, Marcelino Lázaro, Carlos Pantaleón, Jose A. García, Antonio Tazón, Angel Mediavilla:
A nonlinear MESFET model for intermodulation analysis using a generalized radial basis function network. Neurocomputing 25(1-3): 1-18 (1999)
Coauthor Index
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