Selected Talks
March 2022
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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
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A Tutorial on Gaussian Processes and Bayesian Optimization CTTC, Barcelona [slides gps] [slides bo] —- [Virtual Machine (VMplayer) (user: guest, password: guest)] |
July 2021
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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
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A Tutorial on Bayesian Optimization IBPRIA, 2019 [slides] —- [Virtual Machine (VMplayer)] |
July 2019
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Adversarial Alpha-Divergence Minimization Generative Models and Uncertainty Quantification, 2019 [slides] |
Dec 2016
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A Tutorial on Bayesian Optimization Universidad Complutense de Madrid, FuzzyMad 2016 [slides] |
Nov 2016
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Importance Weighted Autoencoders with Random Network Parameters Universidad Autónoma de Madrid, Machine Learning Group [slides] |
Feb 2016
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Predictive Entropy Search for Multi-objective Bayesian Optimization Universidad Autónoma de Madrid, Machine Learning Group [slides] (requires Acrobat Reader) |
May 2015
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Scalable Gaussian Process Classification via Expectation Propagation Workshop on Gaussian Process Approximations, Copenhagen [slides] |
Nov 2014
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A Probabilistic Model for Dirty Multi-task Feature Selection Universidad Autónoma de Madrid, Spain [slides] |
May 2014
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Approximate Inference in Practice: Microsoft’s Xbox True-Skill. Applied Bayesian Methods Master Curse, Universidad Autónoma de Madrid, Spain [slides] |
Nov 2013
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The Lanczos Algorithm. Department of Engineering, Cambridge University, United Kingdom [slides] |
Sep 2013
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Solving Complex Machine Learning Problems using Ensemble Methods. ECML/PKDD workshop, Prague, Czech Republic [slides] |
Aug 2013
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Learning Feature Selection Dependencies in Multi-task Learning. Institute of Computing Technology, Chineese Academy of Sciences, Beijing, China. [slides] |
Sep 2012
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Advanced Topics in Ensemble Learning. ECML/PKDD Tutorial, Bristol, United Kingdom [slides] |
Selected Posters
Dec 2016
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Importance Weighted Autoencoders with Random Network Parameters. NIPS workshop on Bayesian Deep Learning [pdf] |
Jun 2016
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Predictive Entropy Search for Multi-objective Bayesian Optimization. International Conference on Machine Learning [pdf] |
May 2016
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Scalable Gaussian Process Classification via Expectation Propagation. International Conference on Artificial Intelligence and Statistics [pdf] |
Dec 2015
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Stochastic Expectation Propagation for Gaussian Process Classification. NIPS workshop on Approximate Bayesian Inference [pdf] |
Dec 2015
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Predictive Entropy Search for Multi-objective Bayesian Optimizaiton. NIPS workshop on Bayesian Optimizaiton [pdf] |
July 2015
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A Probabilistic Model for Dirty Multi-task Feature Selection. International Conference on Machine Learning (ICML), Lille, France. [pdf] |
Dec 2014
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Mind the Nuisance: Gaussian Process Classification using Privileged Noise. Advances in Neural Information Processing Systems (NIPS), Montreal, Canada. [pdf] |
Dec 2013
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Gaussian Process Conditional Copulas with Applications to Financial Time Series. Advances in Neural Information Processing Systems (NIPS), Lake Tahoe, Nevada, USA. [pdf] |
Dec 2013
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Learning Feature Selection Dependencies in Multi-task Learning. Advances in Neural Information Processing Systems (NIPS), Lake Tahoe, Nevada, USA. [pdf] |
Aug 2013
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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
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Robust Multi-Class Gaussian Process Classification. Advances in Neural Information Processing Systems (NIPS), Granada, Spain. [pdf] |