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David Martínez-Rubio

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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}
    }