Research

Papers

Google Scholar

  • A. Mensch and M. Blondel, “Differentiable dynamic programming for structured prediction and attention,” arXiv preprint arXiv:1802.03676, Feb. 2018. PDF
  • A. Mensch, J. Mairal, B. Thirion, and G. Varoquaux, “Stochastic subsampling for factorizing huge matrices,” IEEE Transactions on Signal Processing, vol. 66, no. 1, pp. 113–128, Jan. 2018. PDF
  • A. Mensch, J. Mairal, D. Bzdok, B. Thirion, and G. Varoquaux, “Learning neural representations of human cognition across many fMRI studies,” in Advances in Neural Information Processing Systems, Dec. 2017, pp. 5885–5895. PDF
  • E. Dohmatob, A. Mensch, G. Varoquaux, and B. Thirion, “Learning brain regions via large-scale online structured sparse dictionary learning,” in Advances in Neural Information Processing Systems, Dec. 2016, pp. 4610–4618. PDF
  • A. Mensch, J. Mairal, B. Thirion, and G. Varoquaux, “Dictionary learning for massive matrix factorization,” in International Conference on Machine Learning, Jun. 2016, pp. 1737–1746. PDF
  • A. Mensch, G. Varoquaux, and B. Thirion, “Compressed online dictionary learning for fast resting-state fMRI decomposition,” in IEEE International Symposium on Biomedical Imaging, Apr. 2016. PDF
  • A. Mensch, E. Piuze, L. Lehnert, A. J. Bakermans, J. Sporring, G. J. Strijkers, and K. Siddiqi, “Connection forms for beating the heart,” in MICCAI Workshop on Statistical Atlases and Computational Models of the Heart, Sep. 2014.

Oral presentations

  • April 2018: Aix-Marseille Université, invited by Caroline Chaux-Moulin Paper / Slides
    • Stochastic Subsampling for Factorizing Huge Matrices
  • April 2018: Facebook Artificial Intelligence Research (Paris, France) Paper / Slides
    • Differentiable Dynamic Programming for Structured Prediction and Attention
  • March 2018: Deep Learning Meetup (Paris, France) Paper / Slides
    • Differentiable Dynamic Programming for Structured Prediction and Attention
  • January 2018: ENS Ulm (Paris, France), invited by Florent Krzakala Paper / Slides
    • Stochastic Subsampling for Factorizing Huge Matrices
  • November 2017: ATR (Kyoto, Japan), invited by Okito Yamashita. Paper / Slides
    • Learning Neural Representations of Human Cognition across Many fMRI Studies
  • July 2017: ISI (Marrakech, Morocco), invited by David Degras. Slides
    • Massive Matrix Factorization for Resting-State fMRI Decomposition
  • October 2016: RecSys FR (Paris, France). Video / SlideShare / Slides
    • Massive Matrix Factorization : Application to collaborative filtering
  • June 2016: ICML (New York, USA). Video / SlideShare / Slides
    • Dictionary Learning for Massive Matrix Factorization

Posters

  • SMAI-MODE 2018: Stochastic Subsampling for Factorizing Huge Matrices
  • MLSS 2017: Stochastic Subsampling for Factorizing Huge Matrices
  • OPT 2017: Stochastic Subsampling for Factorizing Huge Matrices
  • ICML 2016: Dictionary Learning for Massive Matrix Factorization
  • ISBI 2016: Compressed Online Dictionary Learning for Fast fMRI Decomposition
  • OHBM 2016: Compressed Online Dictionary Learning for Fast fMRI Decomposition –>

Arthur Mensch © 2017. All rights reserved.