Díaz-Morales, R., & Navia-Vázquez, Á. (2018). Distributed Nonlinear Semiparametric Support Vector Machine for Big Data Applications on Spark Frameworks. IEEE Transactions on Systems, Man, and Cybernetics: Systems.(ACCEPTED, PREPRINT VERSION)
Díaz-Morales, R., & Navia-Vázquez, Á. (2017). LIBIRWLS: A parallel IRWLS library for full and budgeted SVMs. Knowledge-Based Systems, 136, 183-186.(LINK)
Díaz-Morales, R., & Navia-Vázquez, Á. (2016). Improving the efficiency of IRWLS SVMs using parallel Cholesky factorization. Pattern Recognition Letters, 84, 91-98.(LINK)
Díaz-Morales, R., & Navia-Vázquez, Á. (2016). Efficient parallel implementation of kernel methods. Neurocomputing, 191, 175-186.(LINK)
Navia-Vázquez, A., & Díaz-Morales, R. (2011). Adaptive sigmoidal plant identification using reduced sensitivity recursive least squares. Signal Processing, 91(4), 1066-1070.(LINK)
Navia-Vázquez, A., & Diaz-Morales, R. (2010). Fast error estimation for efficient support vector machine growing. Neurocomputing, 73(4), 1018-1023.(LINK)
Ibáñez Carranza, J.C, Díaz-Morales, R. & Sánchez, J.A. Pattern Recognition in Residential End Uses of Water Using Artificial Neural Networks and Other Machine-Learning Techniques 2017 Computing and Control for the Water Industry (CCWI) (LINK)
Díaz-Morales, R. Cross-Device Tracking: Matching Devices and Cookies Data Mining Workshop (ICDMW), 2015 IEEE International Conference on. (pp. 1699-1704) (LINK)
Omari, A., Díaz-Morales, R., and Choquehuanca-Zevallos, J. J. (2015). Output Correction in HEP using DPGMM NIPS workshop on Applying (machine) Learning to Experimental Physics (LINK)
Díaz-Morales, R., Omari, A., Choquehuanca-Zevallos, J. J., & Garcıa-Hinde, O. (2015). Exploring capacities of SDAs and GBMs in BCI environments. In 7th Intl. IEEE EMBS Conf. on Neural Engineering.(LINK)
Díaz-Morales, R., & Navia-Vázquez, A. (2015). Optimization of AMS using Weighted AUC optimized models. JMLR W&CP, 42, 109-127.(LINK)
Díaz-Morales, R., Molina-Bulla, H. Y., & Navia-Vázquez, A. (2011, July). Parallel semiparametric support vector machines. In Neural Networks (IJCNN), The 2011 International Joint Conference on (pp. 475-481). IEEE.(LINK)
Adil Omari, Juan José Choquehuanca Zevallos, Roberto Diaz Morales Chapter: Nonlinear Feature Extraction for Big Data Analytics Big Data Analytics: Tools and Technology for Effective Planning (LINK)
A Deep Learning use case for water end use detection at Big Data Spain 2017(SLIDES|VIDEO)
Ph.D. Thesis Defense (SLIDES)
Cross-Device Tracking: Matching Devices and Cookies at ICDM 2015(SLIDES|VIDEO)
Optimization of AMS using Weighted AUC optimized models. at NIPS 2014 workshop on HEPML(SLIDES|VIDEO)
Parallel Semiparametric Support Vector Machines at IJCNN 2011(SLIDES)