PhD Theses
- Carlos Ramos Carreño (Supervised by Alberto Suarez González and José Luis Torrecilla Noguerales): Machine Learning with Functional Data: Methodological Advances and Computational Tools (2023)
- Carlos Ruiz Pastor (Supervised by José Dorronsoro and Carlos M. Alaíz Gudín): Advanced Kernel Methods for Multi-Task Learning (2023) [pdf]
- Jesús Prada (Supervised by José Dorronsoro): Uncertainty estimates for SVR models (2022)
- David Díaz Vico (Supervised by José Dorronsoro): Deep learning applied to regression, classification and feature transformation problems (2022) [pdf]
- Simón Rodríguez Santana (Supervised by Daniel Hernández Lobato): Contributions to Approximate Bayesian Inference for Machine Learning (2022) [pdf]
- Carlos Villacampa (Supervised by Daniel Hernández Lobato): Advanced Machine Learning Methods Based on Gaussian Processes (2022) [pdf]
- Eduardo Garrido (Supervised by Daniel Hernández Lobato): Advanced Methods for Bayesian Optimization in Complex Scenarios (2021) [pdf]
- Maryam Sabzevari (Supervised by Gonzalo Martínez-Muñoz and Alberto Suarez): Ensemble Learning in the Presence of Noise (2019) [pdf]
- Bahram Jafrasteh (Supervised by Alberto Suarez and Nader Fathianpour): An intelligent algorithm to improve ore grade and reserve estimation (2018)
- Alberto Torres Barrán (Supervised by José Dorronsoro): Acceleration Methods for Classic Convex Optimization Problems (2017) [pdf] [slides]
- Carlos M. Alaíz Gudín (Supervised by José Dorronsoro): Proximal Methods for Structured Group Features and Correlation Matrix Nearness (2014) [pdf]
- Ángela Fernández Pascual (Supervised by José Dorronsoro and Julia Díaz): Diffusion Methods and Applications (2014) [pdf]
- Irene Rodríguez Luján (Supervised by Carlos Santacruz): A Practical View of Large-Scale Classification: Feature Selection and Real-Time Classification. (2012) [pdf]
- Rubén Ruíz Torrubiano (Supervised by Alberto Suárez): Cardinality constraints and dimensionality reduction in optimization problems. (2012) [pdf]
- Jorge López Lázaro (Supervised by José Dorronsoro): Analysis and Convergence of SMO-like Decomposition and Geometrical Algorithms for Support Vector Machines. (2011) [extended abstract] [pdf]
- Álvaro Barbero Jiménez (Supervised by José Dorronsoro): Efficient Optimization Methods for Regularized Learning: Support Vector Machines and Total-Variation Regularization. (2011) [extended abstract][full text]
- José Miguel Hernández Lobato (Supervised by Alberto Suárez): Balancing flexibility and robustness in machine learning semi-parametric methods and sparse linear models. (2010) [pdf]
- Daniel Hernández Lobato (Supervised by Alberto Suárez): Prediction based on averages over automatically induced learners ensemble methods and Bayesian techniques. (2009) [pdf]
Master Theses
- Francisco Javier Sáez Maldonado (Supervised by Daniel Hernández Lobato and Juan Maroñas Molano): Deep Transformed Gaussian Processes (2023)
- Aitor Sánchez Ferrera (Supervised by José Dorronsoro Ibero): Funciones de pérdida combinadas para problemas de regressión (2022)
- Luis Antonio Ortega Andrés (Supervised by Daniel Hernández-Lobato): Deep Variational Implicit Process (2022)
- Xiangnan Wu (Supervised by José Dorronsoro Ibero): Redes neuronales para la predicción de trayectorias de imágenes NWP (2022)
- Rubén Martínez Sastre (Supervised by José Dorronsoro Ibero): Redes neuronales recurrentes para la predicción de energía eólica y fotovoltaica (2021) [pdf]
- Irene González Velasco (Supervised by Carlos Alaíz Gudín): Interpretación de Modelos de Clasificación mediante la Proyección sobre la Frontera de Decisión (2020)
- David Lopez Ramos (Supervised by Carlos Alaíz Gudín): Regularización Laplaciana en el Espacio Dual para SVMs (2020) [pdf]
- María Cortés Alonso (Supervised by Alberto Suarez): Modelos de aprendizaje automático en la predicción de viento a corto plazo (2020) [pdf]
- Luis Sánchez Calvo (Co-Supervised by Alberto Suarez): Algoritmos de aprendizaje automático para la clasificación de datos funcionales (2020) [pdf]
- Adrián Muñoz Perera (Supervised by Alberto Suarez): Análisis espectral de procesos Gaussianos (2020) [pdf]
- Daniel Fernández Sánchez (Supervised by Daniel Hernández Lobato): Max-value Entropy Search for Multi-objective Bayesian Optimization with Unknown Constraints (2020) [pdf]
- Alex Cañar Gutierrez (Supervised by Gonzalo Martínez Muñoz and Estrella Pulido Cañabate): Estimación de personalidad basado en análisis de movimientos (2019) [pdf]
- Juan Bella Santos (Supervised by José Dorronsoro Ibero): Métodos de aprendizaje automático para detección de anomalías (2019) [pdf]
- Isaac González Gonzáles (Supervised by Ana Gonzalez Marcos y Francisco de Borja Rodríguez Ortíz): Análisis y comparación de extracción de características en señales de audio (2019) [pdf]
- Sara Dorado Alfaro (Supervised by José Dorronsoro Ibero and Ángela Fernández Pascual): Low Rank Approximation and Diffusion Maps (2018) [pdf]
- Carlos Ruiz Pastor (Supervised by José Dorronsoro Ibero and Carlos Alaíz Gudín): Support Vector Machines and Multitask Learning (2018) [pdf]
- Víctor de la Pompa Porras (Supervised by José Dorronsoro Ibero): Procesos Gaussianos para problemas de regresión y estimación de la incertidumbre (2018) [pdf]
- Gonzalo Hernández Muñoz (Supervised by Daniel Hernández Lobato): Deep Gaussian Processes using Expectation Propagation and Monte Carlo Methods (2018) [pdf]
- Miguel Gallego (Supervised by Gonzalo Martínez Muñoz and Estrella Pulido Cañabate): Análisis, comparación y predicción de interacciones de usuarios en cursos online (2018) [pdf]
- Pablo de Viña (Supervised by Gonzalo Martínez Muñoz): Bag of little bootstrap applied to ensembles of classifiers (2018) [pdf]
- Carlos Villacampa Calvo (Supervised by Daniel Hernández Lobato): Procesos Gaussianos para Problemas de Clasificación Multiclase en Conjuntos de Datos Grandes (2017) [pdf]
- Alejandro Catalina Feliú (Supervised by José Dorronsoro): Nesterov Acceleration Schemes for Group Lasso (2017) [pdf]
- Hind Omari (Supervised by Irene Luján): Estimation of classroom occupancy using a multimodal sensory system (2017) [pdf]
- Alvaro Alonso Liso (Supervised by José Dorronsoro): Feature selection for Random Forests and Gradient Boosting Regression (2016) [pdf]
- Daniel López Arias (Supervised by José Dorronsoro): Trend Filtering Techniques for Time Series Analysis (2016) [pdf]
- Maryam Sabzevari (Supervised by Gonzalo Martínez-Muñoz and Alberto Suarez): Ensemble Learning in the Presence of Noise (2016) [pdf]
- Beatriz Bueno Larraz (Supervised by Alberto Suarez and Jose R. Berrendero): Independence measures (2015) [pdf]
- Jesus Prada Alonso (Supervised by José Dorronsoro): SVRs and Uncertainty Estimates (2015) [pdf]
- Jose Luis Jimenez Moro (Supervised by José Dorronsoro): Sparse Modeling and Proximal Optimization in Survival Analysis (2015) [pdf]
- Yvonne Gala Garcia (Supervised by José Dorronsoro): Algoritmos SVM para problemas sobre big data (2013) [pdf]
- Alberto Torres (Supervised by José Dorronsoro): Sparse linear models and proximal optimization. (2013) [pdf] [slides]
- Susana Rojas (Supervised by José Dorronsoro and Jan Larsen): Meta-parameter selection for Support Vector Machines in wind energy forecasting models. (2012) [pdf]
- Javier Di Deco (Supervised by Julia Díaz): Estudio y aplicación de técnicas de aprendizaje automático orientadas al ámbito médico: estimación y explicación de predicciones individuales (2012) [pdf]
- Alejandro Llorente Pinto (Supervised by Alberto Suárez): Analysis of the convergence of Monte Carlo averages. (2012) [pdf]
- Jaime Reguero Álvarez (Supervised by Julia Díaz): Aplicación de las redes bayesianas dinámicas a la predicción de series de datos y a la detección de anomalías. (2011) [pdf]
- Carlos María Alaíz Gudín (Supervised by José Dorronsoro): Advanced Methods for Recurrent Neural Networks Design. (2010) [pdf]
- Ángela Fernández Pascual (Supervised by Julia Díaz): Advanced methods for dimensionality reduction and clustering: Laplacian Eigenmaps and Spectral Clustering. (2010) [pdf]
- Irene Rodríguez Luján (Supervised by Carlos Santa Cruz): Selección de variables mediante programación cuadrática Quadratic Programming Feature Selection (QPFS). (2009) [pdf]
- Jorge López Lázaro (Supervised by José Dorronsoro): On the relationship among the MDM, SMO and SVM-Light Algorithms for training support vector machines. (2008) [pdf]
- Álvaro Barbero Jiménez (Supervised by José Dorronsoro): SVM imbalance correction by conformal kernel transformations. (2008) [pdf]
- José Miguel Hernández Lobato (Supervised by Alberto Suárez): Time series models for measuring market risk technical report. (2007) [pdf]
- Daniel Hernández Lobato (Supervised by Alberto Suárez): Pruning in ordered regression bagging ensembles. (2007) [pdf]