Javier González

Aditya V. Nori

CoRR, 2023

2022

RKHS-SHAP: Shapley Values for Kernel Methods.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Inconsistent Preferences with Gaussian Processes.

[BibT_eX]

[DOI]

Siu Lun Chau

Dino Sejdinovic

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Emulation of physical processes with Emukit.

[BibT_eX]

[DOI]

CoRR, 2021

RKHS-SHAP: Shapley Values for Kernel Methods.

[BibT_eX]

[DOI]

Siu Lun Chau

Dino Sejdinovic

CoRR, 2021

BayesIMP: Uncertainty Quantification for Causal Data Fusion.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Dynamic Causal Bayesian Optimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Preferential Batch Bayesian Optimization.

[BibT_eX]

[DOI]

Eero Siivola

Akash Kumar Dhaka

Michael Riis Andersen

Pablo Garcia Moreno

Aki Vehtari

Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

2020

Automatic Discovery of Privacy-Utility Pareto Fronts.

[BibT_eX]

[DOI]

Proc. Priv. Enhancing Technol., 2020

Good practices for Bayesian Optimization of high dimensional structured spaces.

[BibT_eX]

[DOI]

CoRR, 2020

Structure Mapping for Transferability of Causal Models.

[BibT_eX]

[DOI]

CoRR, 2020

Learning Inconsistent Preferences with Kernel Methods.

[BibT_eX]

[DOI]

Siu Lun Chau

Dino Sejdinovic

CoRR, 2020

Bandit optimisation of functions in the Matérn kernel RKHS.

[BibT_eX]

[DOI]

David Janz

David R. Burt

CoRR, 2020

Multi-task Causal Learning with Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

BOFFIN TTS: Few-Shot Speaker Adaptation by Bayesian Optimization.

[BibT_eX]

[DOI]

Roberto Barra-Chicote

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Causal Bayesian Optimization.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Deep Gaussian Processes for Multi-fidelity Modeling.

[BibT_eX]

[DOI]

CoRR, 2019

Meta-Surrogate Benchmarking for Hyperparameter Optimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Correcting boundary over-Exploration Deficiencies in Bayesian Optimization with Virtual derivative Sign observations.

[BibT_eX]

[DOI]

Michael Riis Andersen

Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018

Structured Variationally Auto-encoded Optimization.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Bayesian Optimization with Tree-structured Dependencies.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

Preferential Bayesian Optimization.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Asymmetric latent semantic indexing for gene expression experiments visualization.

[BibT_eX]

[DOI]

J. Bioinform. Comput. Biol., 2016

Variational Auto-encoded Deep Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the 4th International Conference on Learning Representations, 2016

GLASSES: Relieving The Myopia Of Bayesian Optimisation.

[BibT_eX]

[DOI]

Michael A. Osborne

Neil D. Lawrence

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Batch Bayesian Optimization via Local Penalization.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Time-course window estimator for ordinary differential equations linear in the parameters.

[BibT_eX]

[DOI]

Stat. Comput., 2015

2014

Reproducing kernel Hilbert space based estimation of systems of ordinary differential equations.

[BibT_eX]

[DOI]

Ivan Vujacic

Ernst Wit

Pattern Recognit. Lett., 2014

Generalizing the Mahalanobis distance via density kernels.

[BibT_eX]

[DOI]

Intell. Data Anal., 2014

2013

Functional analysis techniques to improve similarity matrices in discrimination problems.

[BibT_eX]

[DOI]

J. Multivar. Anal., 2013

A New Distance for Data Sets in a Reproducing Kernel Hilbert Space Context.

[BibT_eX]

[DOI]

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2013

On the Generalization of the Mahalanobis Distance.

[BibT_eX]

[DOI]

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2013

2010

Representing functional data using support vector machines.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2010

2009

Combining Functional Data Projections for Time Series Classification.

[BibT_eX]

[DOI]

Proceedings of the Progress in Pattern Recognition, 2009

2008

Functional Learning of Kernels for Information Fusion Purposes.

[BibT_eX]

[DOI]

Proceedings of the Progress in Pattern Recognition, 2008

2007

Spectral Measures for Kernel Matrices Comparison.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 2007

Joint Diagonalization of Kernels for Information Fusion.

[BibT_eX]

[DOI]

Proceedings of the Progress in Pattern Recognition, 2007

2006

Local Linear Approximation for Kernel Methods: The Railway Kernel.

[BibT_eX]

[DOI]