Selected Talks

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]