PhD Theses

  • Maryam Sabzevari (Supervised by Gonzalo Martínez-Muñoz and Alberto Suarez): Ensemble Learning in the Presence of Noise (2019) [pdf]
  • 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

  • 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]
  • 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]
  • David Díaz Vico (Supervised by José Dorronsoro): Deep Neural Networks. (2012) [pdf][slides]
  • 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]