My Publications
You can also find all my publications on Google Scholar.
Conference Publications
Global Riemannian Acceleration in Hyperbolic and Spherical Spaces
D. Martínez-Rubio (2020)
In the 33rd International Conference on Algorithmic Learning Theory, ALT 2022
[BibTeX] [PDF]@article{martinez2020global, title={Global Riemannian Acceleration in Hyperbolic and Spherical Spaces}, author={Mart{\'\i}nez-Rubio, David}, journal={arXiv preprint arXiv:2012.03618}, year={2020} }Decentralized Cooperative Stochastic Bandits
D. Martínez-Rubio, V. Kanade, and P. Rebeschini
In the 32nd Advances in Neural Information Processing Systems, NeurIPS 2019
[BibTeX] [PDF] [Code]@inproceedings{MartinezRubio2018decentralized, author = {David Mart{\'{\i}}nez{-}Rubio and Varun Kanade and Patrick Rebeschini}, editor = {Hanna M. Wallach and Hugo Larochelle and Alina Beygelzimer and Florence d'Alch{\'{e}}{-}Buc and Emily B. Fox and Roman Garnett}, title = {Decentralized Cooperative Stochastic Bandits}, booktitle = {Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada}, pages = {4531--4542}, year = {2019}, url = {https://proceedings.neurips.cc/paper/2019/hash/85353d3b2f39b9c9b5ee3576578c04b7-Abstract.html}, timestamp = {Thu, 21 Jan 2021 15:15:19 +0100}, biburl = {https://dblp.org/rec/conf/nips/Martinez-RubioK19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group
M. Lezcano-Casado, and D. Martínez-Rubio
In the 36th International Conference on Machine Learning, ICML 2019
[BibTeX] [PDF]@inproceedings{DBLP:conf/icml/CasadoM19, author = {Mario Lezcano Casado and David Mart{\'{\i}}nez{-}Rubio}, editor = {Kamalika Chaudhuri and Ruslan Salakhutdinov}, title = {Cheap Orthogonal Constraints in Neural Networks: {A} Simple Parametrization of the Orthogonal and Unitary Group}, booktitle = {Proceedings of the 36th International Conference on Machine Learning, {ICML} 2019, 9-15 June 2019, Long Beach, California, {USA}}, series = {Proceedings of Machine Learning Research}, volume = {97}, pages = {3794--3803}, publisher = , year = {2019}, url = {http://proceedings.mlr.press/v97/lezcano-casado19a.html}, timestamp = {Tue, 11 Jun 2019 15:37:38 +0200}, biburl = {https://dblp.org/rec/conf/icml/CasadoM19.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }Online Learning Rate Adaptation with Hypergradient Descent
A. G. Baydin, R. Cornish, D. Martínez-Rubio, M. Schmidt, and F. Wood
In the 6th International Conference on Learning Representations, ICLR 2018
[BibTeX] [PDF]@inproceedings{DBLP:conf/iclr/BaydinCMSW18, author = {Atilim Gunes Baydin and Robert Cornish and David Mart{\'{\i}}nez{-}Rubio and Mark Schmidt and Frank Wood}, title = {Online Learning Rate Adaptation with Hypergradient Descent}, booktitle = {6th International Conference on Learning Representations, {ICLR} 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings}, publisher = {OpenReview.net}, year = {2018}, url = {https://openreview.net/forum?id=BkrsAzWAb}, timestamp = {Thu, 23 Apr 2020 11:53:22 +0200}, biburl = {https://dblp.org/rec/conf/iclr/BaydinCMSW18.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
Preprints
Fast Algorithms for Packing Proportional Fairness and its Dual
F. Criado, D. Martínez-Rubio, S. Pokutta (2021)
[BibTeX] [PDF]@article{criado2021fast, title={Fast Algorithms for Packing Proportional Fairness and its Dual}, author={Criado, Francisco and Mart{\'\i}nez-Rubio, David and Pokutta, Sebastian}, journal={arXiv preprint arXiv:2109.03678}, year={2021} }Neural Networks are a priori Biased Towards Boolean Functions with Low Entropy
C. Mingard, J. Skalse, G. Valle-Pérez, D. Martínez-Rubio, V. Mikulik, and A. A. Louis (2019)
[BibTeX] [PDF]@article{mingard2019neural, title={Neural networks are a priori biased towards Boolean functions with low entropy}, author={Mingard, Chris and Skalse, Joar and Valle-P{\'e}rez, Guillermo and Mart{\'\i}nez-Rubio, David and Mikulik, Vladimir and Louis, Ard A}, journal={arXiv preprint arXiv:1909.11522}, year={2019} }
Workshop Publications
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators
M. Lezcano-Casado, A.G. Baydin, D. Martínez-Rubio, T.A. Le, F. Wood, L. Heinrich, G. Louppe, K. Cranmer, K. Ng, W. Bhimji and Prabhat
In the Workshop on Deep Learning for Physical Sciences, NIPS 2017
[BibTeX] [PDF]@article{DBLP:journals/corr/abs-1712-07901, author = {Mario Lezcano Casado and Atilim Gunes Baydin and David Mart{\'{\i}}nez{-}Rubio and Tuan Anh Le and Frank D. Wood and Lukas Heinrich and Gilles Louppe and Kyle Cranmer and Karen Ng and Wahid Bhimji and Prabhat}, title = {Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators}, journal = {CoRR}, volume = {abs/1712.07901}, year = {2017}, url = {http://arxiv.org/abs/1712.07901}, archivePrefix = {arXiv}, eprint = {1712.07901}, timestamp = {Tue, 30 Oct 2018 16:42:47 +0100}, biburl = {https://dblp.org/rec/journals/corr/abs-1712-07901.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }
Theses
PhD Thesis
Acceleration in First-Order Optimization Methods: Promenading Beyond Convexity or Smoothness, and Applications
University of Oxford, 2021
[BibTeX] [PDF]@article{martinezrubio2021acceleration, title={Acceleration in First-Order Optimization Methods: Promenading Beyond Convexity or Smoothness, and Applications}, author={Mart{\'\i}nez-Rubio, David}, journal={University of Oxford, Oxford, PhD thesis}, year={2021} }MSc Thesis
Convergence Analysis of an Adaptive Method of Gradient Descent
University of Oxford, 2017
[BibTeX] [PDF]@article{martinezrubio2017convergence, title={Convergence analysis of an adaptive method of gradient descent}, author={Mart{\'\i}nez-Rubio, David}, journal={University of Oxford, Oxford, M. Sc. thesis}, year={2017} }