Journals Books Conferences


o F. J. R. Ruiz, I. Valera and F. Perez-Cruz, (2014). Infinite Factorial Infinite Hidden Markov Model. IEEE Transaction on Pattern Analysis and Machine Intelligence, Accepted

o I. Valera, F. J. R. Ruiz, P. M. Olmos, C. Blanco and F. Perez-Cruz, (2015). Infinite Continuous Feature Model for Psychiatric Comorbidity Analysis Neural Computation, Accepted

o P. G. Moreno, A. Artes-Rodriguez and F. Perez-Cruz, (2015). A Nonparametric Bayesian model for the Multiple Annotators problem. IEEE Transactions on Neural Networks, Submitted

o F. J. R. Ruiz, I. Valera, L. Svensson and F. Perez-Cruz, (2015). Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation. IEEE Transactions on Signal Processing, Submitted

o M. F. Pradier, F. J. R. Ruiz and F. Perez-Cruz, (2015). Prior Design for Dependent Dirichlet Processes: An Application to Marathon Modeling PLOS ONE, Submitted

o J. Cespedes, P. M. Olmos, M. Sanchez-Fernandez and F. Perez-Cruz, (2015). Detection in Large Scale MIMO Systems with Expectation Propagation. IEEE Transactions on Wireless Communications, Submitted.

o F. J. R. Ruiz and F. Perez-Cruz, (2015). A generative model for predicting outcomes in college basketball Journal of Quantitative Analysis in Sports, 11(1): 39 - 52. March

o L. Salamanca, P. M. Olmos, J. J. Murillo-Fuentes, F. Perez-Cruz and S. Verdu, (2015). Approaching the DT Bound Using Linear Codes in the Short Blocklength Regime. IEEE Communications Letters, 19(2):123 - 126. February.

o P. G. Moreno, Y. W. Teh, A. Artes-Rodriguez and F. Perez-Cruz, (2015). Bayesian Nonparametric Crowdsourcing. Journal of Machine Learning Research, 16(Aug):1607 - 1627, 2015

o J. Cespedes, P. M. Olmos, M. Sanchez-Fernandez and F. Perez-Cruz, (2014). Expectation Propagation Detection for High-order High-dimensional MIMO Systems. IEEE Transactions on Communications, 62(8):2840 - 2849. August.

o I. Valera, F. J. R. Ruiz, C. Blanco and F. Perez-Cruz, (2014). Bayesian Nonparametric Comorbidity Analysis of Psychiatric Disorders. Journal of Machine Learning Research, 15(Apr):1215-1247.

o C. G. Taborda, D. Guo and F. Perez-Cruz, (2014). Information-Estimation Relationships over the Binomial and Negative Binomial Models. IEEE Transactions on Information Theory, 60(5):2630 -2646. May.

o L. Salamanca, P. M. Olmos, J. J. Murillo-Fuentes and F. Perez-Cruz, (2013). Tree-Structured Expectation Propagation for LDPC Decoding over BMS Channels. IEEE Transactions on Communications, 61(10):4086-4095. October.

o F. Perez-Cruz, S. Van Vaerenbergh, J. J. Murillo-Fuentes, M. Lazaro-Gredilla and I. Santamaria, (2013). Gaussian Processes for Nonlinear Signal Processing. IEEE Signal Processing Magazine, 30(4):40-50. July.

o R. Santiago-Mozos, F. Perez-Cruz, M. Madden, and A. Artés-Rodríguez, (2014). An Automated Screening System for Tuberculosis. IEEE Journal of Biomedical and Health Informatics, 18(3), 855-862. March.

o P. M. Olmos, J. J. Murillo-Fuentes and F. Perez-Cruz, (2013). Tree-Structure Expectation Propagation for LDPC Decoding over the BEC. IEEE Transactions on Information Theory, 59(6): 3354 - 3377, June.

o L. Salamanca, P. M. Olmos, J. J. Murillo-Fuentes and F. Perez-Cruz, (2013). Tree Expectation Propagation for ML Decoding of LDPC Codes over the BEC. IEEE Transactions on Communications, 61(2): 465 - 473, February

o L. Salamanca, J. J. Murillo-Fuentes and F. Perez-Cruz, (2012). Bayesian Equalization for LDPC Channel Decoding. IEEE Transactions on Signal Processing, 60(5): 2672 - 2676, May.

o P. M. Olmos, L. Salamanca, J. J. Murillo-Fuentes and F. Perez-Cruz, (2012). On the Design of LDPC-Convolutional Ensembles Using the TEP Decoder. IEEE Communications Letters, 16(5): 726 - 729. May.

o M. A. Oquendo, E. Baca-Garcia, A. Artes, F. Perez-Cruz, H. C. Galfalvy, H. Blasco-Fontecilla, D. Madigan and N. Duan, (2012). Machine learning and data mining: strategies for hypothesis generation. Molecular Psychiatry, 17(10):956 - 959. October.

o P. M. Olmos, J. J. Murillo-Fuentes and F. Pérez-Cruz, (2011). Tree-Structured Expectation Propagation for decoding finite-length LDPC codes. IEEE Communications Letters, 15(2):235-237. January

o R. Santiago-Mozos, F. Pérez-Cruz and A. Artés-Rodríguez, (2011). Extended Input Space Support Vector Machine. IEEE Transaction on Neural Networks, 22(1):158-163. January

o D. Tuia, J. Verrelst, L. Alonso, F. Pérez-Cruz and G. Camps-Valls, (2011). Multioutput Support Vector Regression for Remote Sensing Biophysical Parameter Estimation. Geoscience and Remote Sensing Letters, 8(4):804-808. July.

o M. Fresia, F. Pérez-Cruz, H.V. Poor and S. Verdú, (2010). Joint Source and Channel Coding. IEEE Signal Processing Magazine, 27(6):104-113. November .

o F. Pérez-Cruz and S. Kulkarni (2010). Robust and Low Complexity Distributed Kernel Least Squares Learning in Sensor Networks. IEEE Signal Processing Letters, 17(4):355-358. April .

o F. Pérez-Cruz, M. Rodrigues and S. Verdú (2010). MIMO Gaussian Channels with Arbitrary Inputs: Optimal Precoding and Power Allocation. IEEE Transactions on Information Theory, 56(3):1070-1084, March .

o P. M. Olmos, J. J. Murillo-Fuentes and F. Pérez-Cruz, (2010). Joint Nonlinear Channel Equalization and Soft LDPC Decoding with Gaussian Processes. IEEE Transactions on Signal Processing, 58(3):1183-1192, March.

o P. M. Olmos, J. J. Murillo-Fuentes and F. Pérez-Cruz, (2010). Gaussian Processes and its Application to the design of Digital Communication Receivers. In Application of Machine Learning, Edited by Yagang Zhang. In-Tech, February.

o J. J. Murillo-Fuentes and F. Pérez-Cruz, (2009). Gaussian Process Regressors for Multiuser Detection in DS-CDMA Systems. IEEE Transactions on Communications, 57(8):2339-2347, August.

o F. Pérez-Cruz, J. J. Murillo-Fuentes and S. Caro, (2008). Nonlinear Channel Equalization with Gaussian Processes for Regression. IEEE Transactions on Signal Processing, 56(10-2):5283-5286, October.

o F. Pérez-Cruz and J. J. Murillo-Fuentes, (2008). Digital Communication Receivers Using Gaussian Processes for Machine Learning. Journal on Advances in Signal Processing.

o F. Pérez-Cruz, Z. Ghahramani and M. Pontil, (2007). Conditional Graphical Models. In Predicting Structured Data, Edited by G. H. Bakir, T. Hofmann, B. Schölkopf, A. J. Smola, B. Taskar and S. V. N. Vishwanathan. 265-282, MIT Press, September.

o G. Camps, E. Soria, J. Pérez, F. Pérez-Cruz, A. Artés-Rodríguez and N. V. Jiménez-Torres, (2007). Therapeutic Drug Monitoring of Kidney Transplant Recipients Using Profiled Support Vector Machines. IEEE Transactions on Systems, Man and Cybernetics, Part C, 37(3):359-372, May.

o M. Lázaro, I. Santamaría, F. Pérez-Cruz and A. Artés-Rodríguez, (2005). Support vector regression for the simultaneous learning of a multivariate function and its derivatives. Neurocomputing, 69(3):42-61, December.

o M. Lázaro, F. Pérez-Cruz and A. Artés-Rodríguez, (2005). Learning a function and its derivative forcing the support vector expansion. IEEE Signal Processing Letters, 12(3):194-197, March.

o F. Pérez-Cruz, C. Bousoño-Calzón and A. Artés-Rodríguez, (2005). Convergence of the IRWLS procedure to the support vector machine solution. Neural Computation , 17(1):7-18, January.

o S. Salcedo-Sanz, M. de-Prado-Cumplido, M. J. Segovia-Vargas, F. Pérez-Cruz and C. Bousoño-Calzón, (2004). Feature selection methods involving support vector machines for prediction of insolvency in non-life insurance companies. Intelligent Systems in Accounting, Finance and Management, 12(4):261-281, December.

o S. Salcedo-Sanz, F. Pérez-Cruz, G. Camps and C. Bousoño-Calzón, (2004). Enhancing genetic feature selection through restricted search and Walsh analysis. IEEE Transactions on Systems, Man and Cybernetics, Part C, 34(4):398-406, November.

o M. P. Sánchez-Fernández, M. de-Prado-Cumplido, J. Arenas-García and F. Pérez-Cruz, (2004). SVM Multiregression for Non-Linear Channel Estimation in Multiple-Input Multiple-Output Systems. IEEE Transactions on Signal Processing, 58(8):2298-2307, August.

o A. Navia-Vázquez, F. Pérez-Cruz, A. Artés-Rodríguez and A. R. Figueiras-Vidal, (2004). Advantages of Unbiased Support Vector Classifiers for Data Mining Applications. Journal of VLSI Signal Processing Systems, 37(2):223-235, June.

o F. Pérez-Cruz, J. A. Afonso-Rodríguez and J. Giner, (2004). Estimating GARCH models using the support vector machine. Quantitative Finance, 3(3):163-172, June.

o F. Pérez-Cruz and O. Bousquet, (2004). Kernel methods and their potential use in signal processing. IEEE SignalProcessing Magazine, 21(3):57-65, May.

o J. Weston, F Pérez-Cruz, O. Bousquet, O. Chapelle, A. Elisseeff and B. Schölkopf, (2003). Feature Selection and Transduction for Prediction of Molecular Bioactivity for Drug Design. Bioinformatics 19(6):764-771, April.

o F. Pérez-Cruz, A. Navia-Vázquez, A. R. Figueiras-Vidal and A. Artés-Rodríguez, (2003). Empirical Risk Minimization for Support Vector Classifiers. IEEE Transactions on Neural Networks, 14(2):296-303, March.

o F. Pérez-Cruz, J. Weston, D. J. L. Herrmann and B. Schölkopf, (2003). Extension of the nu-SVM Range for Classification. In Advances in Learning Theory: Methods, Models and Applications, Edited by J.A.K. Suykens, G. Horvath, S. Basu, C. Micchelli and J. Vandewalle. 179-196, IOS Press.

o G. Camps, E. Soria, J. Pérez, F. Pérez-Cruz, A. R. Figueiras-Vidal and A. Artés-Rodríguez, (2002). Cyclosporine concentration prediction using clustering and support vector regression methods. IEE Electronic Letters, 38(12):568-570, June.

o A. Navia-Vázquez, F. Pérez-Cruz, A. Artés-Rodríguezand A. R. Figueiras-Vidal, (2001). Weighted Least Squares Training of Support Vectors Classifiers which Leads to Compact and Adaptive Schemes. IEEE Transactions on Neural Networks, 12(5):1047-1059. September.

o F. Pérez-Cruz, P. Alarcón-Diana, A. Navia-Vázquez and A. Artés-Rodríguez, (2001). SVC-Based Equalizer for Burst TDMA Transmissions. Signal Processing, 81(8):1681-1693. August.

o F. J. González-Serrano, F. Pérez-Cruz and A. Artés-Rodríguez, (1998). Reduced-complexity equaliser for nonlinear channels. IEE Electronic Letters, 34(9):856-858, April.