Marcelino Lázaro

According to our database, Marcelino Lázaro authored at least 39 papers between 1999 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

One-step Bayesian example-dependent cost classification: The OsC-MLP method.

Javier Mediavilla-Relaño, Marcelino Lázaro

Neural Networks, 2024

COCOA: Cost-Optimized COunterfactuAl explanation method.

Javier Mediavilla-Relaño, Marcelino Lázaro

Inf. Sci., 2024

2023

Neural network for ordinal classification of imbalanced data by minimizing a Bayesian cost.

Marcelino Lázaro, Aníbal R. Figueiras-Vidal

Pattern Recognit., May, 2023

Imbalance example-dependent cost classification: A Bayesian based method.

Javier Mediavilla-Relaño, Marcelino Lázaro, Aníbal R. Figueiras-Vidal

Expert Syst. Appl., 2023

2021

A Bayes Risk Minimization Machine for Example-Dependent Cost Classification.

Marcelino Lázaro, Aníbal R. Figueiras-Vidal

IEEE Trans. Cybern., 2021

2020

Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification.

Marcelino Lázaro, Francisco Herrera, Aníbal R. Figueiras-Vidal

Inf. Sci., 2020

2019

A Principled Two-Step Method for Example-Dependent Cost Binary Classification.

Javier Mediavilla-Relaño, Aitor Gutiérrez-López, Marcelino Lázaro, Aníbal R. Figueiras-Vidal

Proceedings of the From Bioinspired Systems and Biomedical Applications to Machine Learning, 2019

2018

Training neural network classifiers through Bayes risk minimization applying unidimensional Parzen windows.

Marcelino Lázaro, Monson H. Hayes, Aníbal R. Figueiras-Vidal

Pattern Recognit., 2018

2017

Class Switching according to Nearest Enemy Distance for learning from highly imbalanced data-sets.

Sergio González, Salvador García, Marcelino Lázaro, Aníbal R. Figueiras-Vidal, Francisco Herrera

Pattern Recognit., 2017

2016

Decentralized detection for censored binary observations with statistical dependence.

Marcelino Lázaro

Signal Process., 2016

2015

Classification of Binary Imbalanced Data Using A Bayesian Ensemble of Bayesian Neural Networks.

Marcelino Lázaro, Francisco Herrera, Aníbal R. Figueiras-Vidal

Proceedings of the Engineering Applications of Neural Networks, 2015

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

Optimal Neyman-Pearson fusion in two-dimensional sensor networks with serial architecture and dependent observations.

Jorge Plata-Chaves, Marcelino Lázaro, Antonio Artés-Rodríguez

Proceedings of the 14th International Conference on Information Fusion, 2011

2010

Closed-form error exponent for the Neyman-Pearson fusion of two-dimensional Markov local decisions.

Jorge Plata-Chaves, Marcelino Lázaro

Proceedings of the 18th European Signal Processing Conference, 2010

2009

Optimal Sensor Selection in Binary Heterogeneous Sensor Networks.

Marcelino Lázaro, Matilde Sánchez Fernández, Antonio Artés-Rodríguez

IEEE Trans. Signal Process., 2009

Blind equalization using the IRWLS formulation of the support vector machine.

Marcelino Lázaro, Jonathan González-Olasola

Signal Process., 2009

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

Proceedings of the International Joint Conference on Neural Networks, 2007

Optimal Sensor Selection in Heterogeneous Sensor Networks.

Marcelino Lázaro, Antonio Artés-Rodríguez

Proceedings of the IEEE International Conference on Acoustics, 2007

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

Proceedings of the Fourth IEEE International Conference on Advanced Video and Signal Based Surveillance, 2007

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

Learning a function and its derivative forcing the support vector expansion.

Marcelino Lázaro, Fernando Pérez-Cruz, Antonio Artés-Rodríguez

IEEE Signal Process. Lett., 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

Decentralized detection in dense sensor networks with censored transmissions.

Antonio Artés-Rodríguez, Marcelino Lázaro, Matilde Sánchez Fernández

Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

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

Blind restoration of binary signals using a line spectrum fitting approach.

Javier Vía, Ignacio Santamaría, Marcelino Lázaro

Proceedings of the 2004 12th European Signal Processing Conference, 2004

Multidimensional SVM to include the samples of the derivatives in the reconstruction of a function.

Fernando Pérez-Cruz, Marcelino Lázaro, Antonio Artés-Rodríguez

Proceedings of the 2004 12th European Signal Processing Conference, 2004

Blind equalization of multilevel signals using support vector machines.

Marcelino Lázaro, Ignacio Santamaría, Javier Vía, Deniz Erdogmus

Proceedings of the 2004 12th European Signal Processing Conference, 2004

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, Luis Vielva

Signal Process., 2003

A new EM-based training algorithm for RBF networks.

Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón

Neural Networks, 2003

Modeling Nonlinear Power Amplifiers in OFDM Systems from Subsampled Data: A Comparative Study Using Real Measurements.

Ignacio Santamaría, Jesús Ibáñez, Marcelino Lázaro, Carlos Pantaleón, Luis Vielva

EURASIP J. Adv. Signal Process., 2003

Support vector machine for the simultaneous approximation of a function and its derivative.

Marcelino Lázaro, Ignacio Santamaría, Fernando Pérez-Cruz, Antonio Artés-Rodríguez

Proceedings of the NNSP 2003, 2003

Matched pdf-based blind equalization.

Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón, Deniz Erdogmus, José C. Príncipe

Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

2001

Neural networks for large- and small-signal modeling of MESFET/HEMT transistors.

Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón

IEEE Trans. Instrum. Meas., 2001

Accelerating the Convergence of EM-Based Training Algorithms for RBF Networks.

Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón

Proceedings of the Connectionist Models of Neurons, 2001

A regularized digital filtering technique for the simultaneous reconstruction of a function and its derivatives.

Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón

Proceedings of the 2001 8th IEEE International Conference on Electronics, 2001

2000

A smooth and derivable large-signal model for microwave HEMT transistors.

Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón

Proceedings of the IEEE International Symposium on Circuits and Systems, 2000

Neuronal Architecture for Waveguide Inductive Iris Bandpass Filter Optimization.

Angel Mediavilla, Antonio Tazón, J. A. Pereda, Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

A Modular Neural Network for Global Modeling of Microwave Transistors.

Marcelino Lázaro, Ignacio Santamaría, Carlos Pantaleón, Cesar Navarro, Antonio Tazón, Tomás Fernández Ibáñez

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1999

A nonlinear MESFET model for intermodulation analysis using a generalized radial basis function network.

Ignacio Santamaría, Marcelino Lázaro, Carlos Pantaleón, Jose A. García, Antonio Tazón, Angel Mediavilla

Neurocomputing, 1999