A nonlinear MESFET model for intermodulation analysis using a generalized radial basis function network. - Ignacio Santamaría; Marcelino Lázaro; Carlos Pantaleón; Jose A. García 002; Antonio Tazón; Angel Mediavilla (Neurocomputing, 1999)

A Modular Neural Network for Global Modeling of Microwave Transistors. - Marcelino Lázaro; Ignacio Santamaría; Carlos Pantaleón; Cesar Navarro; Antonio Tazón; Tomás Fernández Ibáñez (IJCNN (4), 2000)

Neuronal Architecture for Waveguide Inductive Iris Bandpass Filter Optimization. - Angel Mediavilla; Antonio Tazón; J. A. Pereda; Marcelino Lázaro; Ignacio Santamaría; Carlos Pantaleón (IJCNN (4), 2000)

A smooth and derivable large-signal model for microwave HEMT transistors. - Marcelino Lázaro; Ignacio Santamaría; Carlos Pantaleón (ISCAS, 2000)

A regularized digital filtering technique for the simultaneous reconstruction of a function and its derivatives. - Marcelino Lázaro; Ignacio Santamaría; Carlos Pantaleón (ICECS, 2001)

Accelerating the Convergence of EM-Based Training Algorithms for RBF Networks. - Marcelino Lázaro; Ignacio Santamaría; Carlos Pantaleón (IWANN (1), 2001)

Neural networks for large- and small-signal modeling of MESFET/HEMT transistors. - Marcelino Lázaro; Ignacio Santamaría; Carlos Pantaleón (IEEE Trans. Instrum. Meas., 2001)

Matched pdf-based blind equalization. - Marcelino Lázaro; Ignacio Santamaría; Carlos Pantaleón; Deniz Erdogmus; José C. Príncipe (ICASSP (4), 2003)

Support vector machine for the simultaneous approximation of a function and its derivative. - Marcelino Lázaro; Ignacio Santamaría; Fernando Pérez-Cruz; Antonio Artés-Rodríguez (NNSP, 2003)

Modeling Nonlinear Power Amplifiers in OFDM Systems from Subsampled Data: A Comparative Study Using Real Measurements. - Ignacio Santamaría; Jesús Ibáñez 002; Marcelino Lázaro; Carlos Pantaleón; Luis Vielva (EURASIP J. Adv. Signal Process., 2003)

A new EM-based training algorithm for RBF networks. - Marcelino Lázaro; Ignacio Santamaría; Carlos Pantaleón (Neural Networks, 2003)

A regularized technique for the simultaneous reconstruction of a function and its derivatives with application to nonlinear transistor modeling. - Marcelino Lázaro; Ignacio Santamaría; Carlos Pantaleón; Jesús Ibáñez 002; Luis Vielva (Signal Process., 2003)

Blind equalization of multilevel signals using support vector machines. - Marcelino Lázaro; Ignacio Santamaría; Javier Vía; Deniz Erdogmus (EUSIPCO, 2004)

Multidimensional SVM to include the samples of the derivatives in the reconstruction of a function. - Fernando Pérez-Cruz; Marcelino Lázaro; Antonio Artés-Rodríguez (EUSIPCO, 2004)

Blind restoration of binary signals using a line spectrum fitting approach. - Javier Vía; Ignacio Santamaría; Marcelino Lázaro (EUSIPCO, 2004)

Adaptive blind deconvolution of linear channels using Renyi's entropy with Parzen window estimation. - Deniz Erdogmus; Kenneth E. Hild II; José C. Príncipe; Marcelino Lázaro; Ignacio Santamaría (IEEE Trans. Signal Process., 2004)

Decentralized detection in dense sensor networks with censored transmissions. - Antonio Artés-Rodríguez; Marcelino Lázaro; Matilde Sánchez Fernández (ICASSP (4), 2005)

Support Vector Regression for the simultaneous learning of a multivariate function and its derivatives. - Marcelino Lázaro; Ignacio Santamaría; Fernando Pérez-Cruz; Antonio Artés-Rodríguez (Neurocomputing, 2005)

Learning a function and its derivative forcing the support vector expansion. - Marcelino Lázaro; Fernando Pérez-Cruz; Antonio Artés-Rodríguez (IEEE Signal Process. Lett., 2005)

Stochastic blind equalization based on PDF fitting using Parzen estimator. - Marcelino Lázaro; Ignacio Santamaría; Deniz Erdogmus; Kenneth E. Hild II; Carlos Pantaleón; José C. Príncipe (IEEE Trans. Signal Process., 2005)

Real-time tracking and identification on an intelligent IR-based surveillance system. - Juan C. Alonso-Bayal; Ricardo Santiago-Mozos; José M. Leiva-Murillo; Marcelino Lázaro; Antonio Artés-Rodríguez (AVSS, 2007)

Optimal Sensor Selection in Heterogeneous Sensor Networks. - Marcelino Lázaro; Antonio Artés-Rodríguez (ICASSP (2), 2007)

A New Cost Function for Binary Classification Problems Based on the Distributions of the Soft Output for Each Class. - Marcelino Lázaro; José M. Leiva-Murillo; Antonio Artés-Rodríguez; Aníbal R. Figueiras-Vidal (IJCNN, 2007)

Blind equalization using the IRWLS formulation of the support vector machine. - Marcelino Lázaro; Jonathan González-Olasola (Signal Process., 2009)

Optimal Sensor Selection in Binary Heterogeneous Sensor Networks. - Marcelino Lázaro; Matilde Sánchez Fernández; Antonio Artés-Rodríguez (IEEE Trans. Signal Process., 2009)

Closed-form error exponent for the Neyman-Pearson fusion of two-dimensional Markov local decisions. - Jorge Plata-Chaves; Marcelino Lázaro (EUSIPCO, 2010)

Optimal Neyman-Pearson fusion in two-dimensional sensor networks with serial architecture and dependent observations. - Jorge Plata-Chaves; Marcelino Lázaro; Antonio Artés-Rodríguez (FUSION, 2011)

Closed-Form Error Exponent for the Neyman-Pearson Fusion of Dependent Local Decisions in a One-Dimensional Sensor Network. - Jorge Plata-Chaves; Marcelino Lázaro (IEEE Trans. Signal Process., 2011)

Classification of Binary Imbalanced Data Using A Bayesian Ensemble of Bayesian Neural Networks. - Marcelino Lázaro; Francisco Herrera; Aníbal R. Figueiras-Vidal (EANN, 2015)

Decentralized detection for censored binary observations with statistical dependence. - Marcelino Lázaro (Signal Process., 2016)

Class Switching according to Nearest Enemy Distance for learning from highly imbalanced data-sets. - Sergio González; Salvador García 001; Marcelino Lázaro; Aníbal R. Figueiras-Vidal; Francisco Herrera (Pattern Recognit., 2017)

Training neural network classifiers through Bayes risk minimization applying unidimensional Parzen windows. - Marcelino Lázaro; Monson H. Hayes; Aníbal R. Figueiras-Vidal (Pattern Recognit., 2018)

A Principled Two-Step Method for Example-Dependent Cost Binary Classification. - Javier Mediavilla-Relaño; Aitor Gutiérrez-López; Marcelino Lázaro; Aníbal R. Figueiras-Vidal (IWINAC (2), 2019)

Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification. - Marcelino Lázaro; Francisco Herrera; Aníbal R. Figueiras-Vidal (Inf. Sci., 2020)

A Bayes Risk Minimization Machine for Example-Dependent Cost Classification. - Marcelino Lázaro; Aníbal R. Figueiras-Vidal (IEEE Trans. Cybern., 2021)

Imbalance example-dependent cost classification: A Bayesian based method. - Javier Mediavilla-Relaño; Marcelino Lázaro; Aníbal R. Figueiras-Vidal (Expert Syst. Appl., 2023)

Neural network for ordinal classification of imbalanced data by minimizing a Bayesian cost. - Marcelino Lázaro; Aníbal R. Figueiras-Vidal (Pattern Recognit., 2023)

COCOA: Cost-Optimized COunterfactuAl explanation method. - Javier Mediavilla-Relaño; Marcelino Lázaro (Inf. Sci., 2024)

One-step Bayesian example-dependent cost classification: The OsC-MLP method. - Javier Mediavilla-Relaño; Marcelino Lázaro (Neural Networks, 2024)