Gauthier Gidel

Ph.D. Candidate
Université de Montréal - DIRO
Mila Send an email


I am a Ph.D. candidate supervised by Simon Lacoste-Julien at DIRO and Mila. I graduated from ENS Ulm and Université Paris-Saclay. During my Ph.D., I have been an intern at Sierra, ElementAI and DeepMind. My work focuses on optimization applied to machine learning---more details in my resume (early 2018).

Link to my Google scholar.


Research interests

My research aims at getting a better understanding of differentiable games and more generally optimization for modern machine learning. Particularly, I am interested in the following questions:
  • What are the funtamental reasons behind the great successes of adversarial formulations?
  • What are the new difficulties and issues arising when training models though differentiable games and how to tackle them?
  • How can we design more efficient training methods for differentiable games?
  • What is generalization and how is it impacted by the choice of the training method?

I identify to the fields of machine learning (JMLR, NeurIPS, ICML, AISTATS, COLT, and ICLR) and optimization (SIAM OP)

[NEW!]


ICML and COLT decisions are out and I got one paper accepted to each conference! AISTATS decisions are out and I got two papers accepted to the main conference! NeurIPS decisions are out and I got four papers accepted to the main conference!

Preprints - Publications - Manuscripts


  • 5
    Adaptive Three Operator Splitting

    Fabian Pedregosa, Gauthier Gidel.
    Proceedings of the 35th International Conference on Machine Learning (ICML), 2018.

    Paper Poster Slides bibtex arXiv
    @inproceedings{pedregosa2018adaptive,
      author      = {Pedregosa, Fabian and Gidel, Gauthier},
      title       = {Adaptive Three Operator Splitting},
      booktitle   = {ICML},
      year        = {2018} 
                    }

  • 4
    Frank-Wolfe Splitting via Augmented Lagrangian Method

    Gauthier Gidel, Fabian Pedregosa and Simon Lacoste-Julien.
    Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 2018. (ORAL, TOP 5% of submitted papers)

    Paper Webpage Poster Slides bibtex
    @inproceedings{gidel2018fwal,
      author      = {Gidel, Gauthier and Pedregosa, Fabian and Lacoste-Julien, Simon},
      title       = {Frank-Wolfe Splitting via Augmented Lagrangian Method},
      booktitle   = {AISTATS},
      year        = {2018} 
                  }

  • 2
    Frank-Wolfe Algorithms for Saddle Point Problems

    Gauthier Gidel, Tony Jebara and Simon Lacoste-Julien.
    Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS), 2017.

    Paper bibtex arXiv
    @inproceedings{gidel2017saddle,
      author      = {Gidel, Gauthier and Jebara, Tony and Lacoste-Julien, Simon},
      title       = {{F}rank-{W}olfe Algorithms for Saddle Point Problems},
      booktitle     = {Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS)},
      year        = {2017} 
                    }
    HAL Code Project Poster

    Accepted as an oral presentation at the NeurIPS OPT2016 workshop
    (TOP 10% of accepted submissions).
  • 1
    Extensions de l’algorithme de Frank-Wolfe pour la recherche de points selles. (In French)

    Gauthier Gidel.
    Introduction au domaine de recherche (Equivalent of Master's thesis) au DMA, ENS 2016.


Talks


2019
2018
2017 2016

Reviewing


  • NeurIPS 2018 Top 200 reviewer.
  • ICLR 2019.
  • AISTATS 2019.
  • ICML 2019 (top 5% reviewer).

  • Teaching Experience


    Mathematics Examiner in CPGE (most competitive undergrad program in France)


    Contact


    Gauthier Gidel
    Pavillon André-Aisenstadt
    2920 Chemin de la Tour, office 3331
    Montreal, QC
    H3T 1J4 CANADA

    © 2019