Talks and Posters

Selected Talks

June 2023
 Gaussian Processes and Bayesian Optimizaton
MLAS Summer School 2023, UPM [slides GPs 1] [slides GPs 2] [slides GPs 3] [slides BO]
Notebooks: [Github-link]
March 2022
 A Tutorial on Bayesian Optimization
TresPass Summer School 2022, EPS, UAM [slides bo] —- [Virtual Machine (VMplayer) (user: guest, password: guest)]
Notebooks: [Single-Objective BO] [Constrained Single-Objective BO] [Multi-Objective BO]
March 2022
 A Tutorial on Gaussian Processes and Bayesian Optimization
CTTC, Barcelona [slides gps] [slides bo] —- [Virtual Machine (VMplayer) (user: guest, password: guest)]
July 2021
 A Tutorial on Gaussian Processes and Bayesian Optimization
AERFAI Summer school, 2021 [slides gps] [slides bo] —- [Virtual Machine (VMplayer) (user: guest, password: guest)]
July 2019
 A Tutorial on Bayesian Optimization
IBPRIA, 2019 [slides] —- [Virtual Machine (VMplayer)]
July 2019
 Adversarial Alpha-Divergence Minimization
Generative Models and Uncertainty Quantification, 2019 [slides]
Dec 2016
 A Tutorial on Bayesian Optimization
Universidad Complutense de Madrid, FuzzyMad 2016 [slides]
Nov 2016
 Importance Weighted Autoencoders with Random Network Parameters
Universidad Autónoma de Madrid, Machine Learning Group [slides]
Feb 2016
 Predictive Entropy Search for Multi-objective Bayesian Optimization
Universidad Autónoma de Madrid, Machine Learning Group [slides] (requires Acrobat Reader)
May 2015
 Scalable Gaussian Process Classification via Expectation Propagation
Workshop on Gaussian Process Approximations, Copenhagen [slides]
Nov 2014
 A Probabilistic Model for Dirty Multi-task Feature Selection
Universidad Autónoma de Madrid, Spain [slides]
May 2014
 Approximate Inference in Practice: Microsoft’s Xbox True-Skill.
Applied Bayesian Methods Master Curse, Universidad Autónoma de Madrid, Spain [slides]
Nov 2013
 The Lanczos Algorithm.
Department of Engineering, Cambridge University, United Kingdom [slides]
Sep 2013
 Solving Complex Machine Learning Problems using Ensemble Methods.
ECML/PKDD workshop, Prague, Czech Republic [slides]
Aug 2013
 Learning Feature Selection Dependencies in Multi-task Learning.
Institute of Computing Technology, Chineese Academy of Sciences, Beijing, China. [slides]
Sep 2012
 Advanced Topics in Ensemble Learning.
ECML/PKDD Tutorial, Bristol, United Kingdom [slides]

Selected Posters

Dec 2016
 Importance Weighted Autoencoders with Random Network Parameters.
NIPS workshop on Bayesian Deep Learning [pdf]
Jun 2016
 Predictive Entropy Search for Multi-objective Bayesian Optimization.
International Conference on Machine Learning [pdf]
May 2016
 Scalable Gaussian Process Classification via Expectation Propagation.
International Conference on Artificial Intelligence and Statistics [pdf]
Dec 2015
 Stochastic Expectation Propagation for Gaussian Process Classification.
NIPS workshop on Approximate Bayesian Inference [pdf]
Dec 2015
 Predictive Entropy Search for Multi-objective Bayesian Optimizaiton.
NIPS workshop on Bayesian Optimizaiton [pdf]
July 2015
 A Probabilistic Model for Dirty Multi-task Feature Selection.
International Conference on Machine Learning (ICML), Lille, France. [pdf]
Dec 2014
 Mind the Nuisance: Gaussian Process Classification using Privileged Noise.
Advances in Neural Information Processing Systems (NIPS), Montreal, Canada. [pdf]
Dec 2013
 Gaussian Process Conditional Copulas with Applications to Financial Time Series.
Advances in Neural Information Processing Systems (NIPS), Lake Tahoe, Nevada, USA. [pdf]
Dec 2013
 Learning Feature Selection Dependencies in Multi-task Learning.
Advances in Neural Information Processing Systems (NIPS), Lake Tahoe, Nevada, USA. [pdf]
Aug 2013
 Statistical Tests for the Detection of the Arrow of Time in Vector Autoregressive Models.
International Joint Conference in Artificial Intelligence, Beijing, China. [pdf]
Dec 2011
 Robust Multi-Class Gaussian Process Classification.
Advances in Neural Information Processing Systems (NIPS), Granada, Spain. [pdf]