Julien Audiffren

Brief Bio

I am currently (Since sept 2017) a Senior Researcher in the Exascale Infolab laboratory, at the University of Fribourg, in Switzerland. Previously, I was a postdoctoral researcher in the CMLA, a laboratory of Ens Paris Saclay.

Research Interests

Multi-armed bandits; Inverse Reinforcement Learning; Machine Learning for Medical Data; Kernel Theory.


  1. Laura Rettig, Julien Audiffren, and Philippe Cudré-Mauroux. “Fusing Vector Space Models for Domain-Specific Applications.” In IEEE 31st International Conference on Tools with Artificial Intelligence, ICTAI 2019, 2019. Bibtex PDF
  2. Alisa Smirnova, Julien Audiffren, and Philippe Cudré-Mauroux. “Distant Supervision from Knowledge Graphs.” In Encyclopedia of Big Data Technologies., 2019. Bibtex PDF
  3. Ioannis Bargiotas, Julien Audiffren, Nicolas Vayatis, Pierre-Paul Vidal, Stephane Buffat, Alain P Yelnik, and Damien Ricard. “On the Importance of Local Dynamics in Statokinesigram: A Multivariate Approach for Postural Control Evaluation in Elderly.” PLOS ONE 13, no. 2 (2018): e0192868. Bibtex
  4. Julien Audiffren, and Hachem Kadri. “m-Power Regularized Least Squares Regression.” In Neural Networks (IJCNN), 2017 International Joint Conference On, 1080–86. IEEE, 2017. Bibtex
  5. Julien Audiffren, and Liva Ralaivola. “Bandits Dueling on Partially Ordered Sets.” In Advances in Neural Information Processing Systems, 2126–35, 2017. Bibtex
  6. Julien Audiffren, and Emile Contal. “Preprocessing the Nintendo Wii Board Signal to Derive More Accurate Descriptors of Statokinesigrams.” Sensors 16, no. 8 (2016): 1208. Bibtex
  7. Thomas Moreau, and Julien Audiffren. “Post Training in Deep Learning with Last Kernel.” ArXiv Preprint ArXiv:1611.04499, 2016. Bibtex
  8. Julien Audiffren, Ioannis Bargiotas, Nicolas Vayatis, Pierre-Paul Vidal, and Damien Ricard. “A Non Linear Scoring Approach for Evaluating Balance: Classification of Elderly as Fallers and Non-Fallers.” PLoS One 11, no. 12 (2016): e0167456. Bibtex
  9. Julien Audiffren, and Hachem Kadri. “Online Learning with Operator-Valued Kernels.” In ESANN, 2015. Bibtex
  10. Julien Audiffren, Michal Valko, Alessandro Lazaric, and Mohammad Ghavamzadeh. “Maximum Entropy Semi-Supervised Inverse Reinforcement Learning..” In IJCAI, 3315–21, 2015. Bibtex
  11. Julien Audiffren, and Liva Ralaivola. “Cornering Stationary and Restless Mixing Bandits with Remix-UCB.” In NIPS, 2015. Bibtex
  12. Hachem Kadri, Emmanuel DUFLOS, philippe preux, stephane canu, Alain Rakotomamonjy, and Julien Audiffren. “Operator-Valued Kernels for Learning from Functional Response Data.” JMLR, 2015. Bibtex
  13. J Audiffren, R Barrois-Müller, C Provost, É Chiarovano, L Oudre, T Moreau, C Truong, et al. “Évaluation De l’Équilibre Et Prédiction Des Risques De Chutes En Utilisant Une Wii Board Balance.” Neurophysiologie Clinique/Clinical Neurophysiology 4, no. 45 (2015): 403. Bibtex
  14. Julien Audiffren, and Etienne Pardoux. “Muller’s Ratchet Clicks in Finite Time.” Stochastic Processes and Their Applications 123, no. 6 (2013): 2370–97. Bibtex
  15. Julien Audiffren, and Hachem Kadri. “Stability of Multi-Task Kernel Regression Algorithms.” In ACML, 2013. Bibtex
  16. Julien Audiffren, and Hachem Kadri. “Online Learning with Multiple Operator-Valued Kernels.” ArXiv Preprint ArXiv:1311.0222, 2013. Bibtex
  17. Julien Audiffren. “Equivalence of the Fleming-Viot and Look-down Models of Muller’s Ratchet,” 2012. Bibtex
  18. Pierre Humbert, Julien Audiffren, Clément Dubost, and Laurent Oudre. “Learning from an Expert,” n.d. Bibtex