Lilian Besson

Mathematician & Computer Scientist • Passionate teacher and researcher.

📜   Short Bio

Hello ! I am Lilian Besson, a former student in Mathematics and Computer Science at ENS de Cachan. I am a passionate programmer, open-source enthusiast and young researcher in machine learning, learning theory and cognitive radio. I also love to cook and meet people, to travel and exchange, to bike or hike. 👨 I use the he/him pronouns.

Since October 2016, until July 2019:

📰   News

🔬   Research

For my Ph.D., my research is in applied machine learning, focused on low-cost online learning algorithm with limited feedback (bandit feedback), mainly applied to cognitive radio problems for Opportunistic Spectrum Access and setting up reliable network access protocol for the future Internet of Things networks. By studying and applying classical and recent Multi-Armed Bandit algorithms to carefully designed radio models, we are able to prove some performance guarantees, both numerically in simulations and theoretically with statistical proofs.

  • 11 Research talks and posters
    (since 2017)
  • 9 Research articles
    (5 published, 1 sent)
  • 2 PhD advisors
    and collaboration with 2 PhD student and postdoc
  • 2 Higher Education institutes where I teach in Rennes
  • 1 Research software
    (and many personal projects!)

📚   Publications logo Orcid arXiv DBLP DBLP IdHAL Google Scholar HALtools
List of the PDF of my articles


  1. R. Bonnefoi, J. Manco-Vasquez, L. Besson, C. Moy.
    Upper-Confidence Bound for Channel Selection in LPWA Networks with Retransmissions.
    September 2018.
    [ PDF* ] • [ Code (MATLAB) ]
  2. L. Besson & E. Kaufmann.
    What Doubling-Trick Can and Can't Do for Multi-Armed Bandits. September 2018.
    [ PDF ] • [ Mobile version ] • [ arXiv ] • [ HAL ] • [ BibTeX ] • [ Code (LaTeX) ] • [ Code ]
  3. L. Besson. 🔬 🎰 SMPyBandits: an Open-Source Research Framework for Single and Multi-Players Multi-Arms Bandits (MAB) Algorithms in Python. July 2018. PyPI version Documentation Status Build Status GitHub forks GitHub stars GitHub watchers
    [ PDF ] [ PDF* (long version) ] • [ HAL ] • [ BibTeX ] • [ Code ] • [ Documentation ]
  4. L. Besson. A Note on the Ei Function and a Useful Sum-Inequality. February 2018.
    [ PDF ] • [ HAL ] • [ BibTeX ] • [ Code ]

Communications in International Conferences

  1. L. Besson, R. Bonnefoi, C. Moy.
    MALIN: an Implementation of Multi-Armed Bandits Learning Schemes for Internet-of-things Networks
    Article accepted to WCNC (Wireless Communication and Networks Conference), Marrakech, Morocco. April 2019.
    [ PDF* ] • [ YouTube Video ] • [ Code (GNU Radio) ]
  2. L. Besson, R. Bonnefoi, C. Moy.
    MALIN: Multi-Arm bandit Learning for Iot Networks with GRC: A TestBed Implementation and Demonstration that Learning Helps.
    Demonstration presented at the ICT (International Conference on Communication), Saint-Malo, France. June 2018.
    [ PDF* ] • [ Poster ] • [ YouTube Video ] • [ Code (GNU Radio) ]
    More details… The demo implements a toy wireless system, with one IoT object communicating with a gateway (or base station) and trying to find the frequency channel which is the less perturbated by a random interfering traffic, by using reinforcement learning. We use three USRP cards by National Instruments for the random traffic, the IoT object and the gateway. It is based on our CROWNCOM 2017 article. See also this document. Here is a 5-minute video I made to explain this demonstration.
  3. L. Besson & E. Kaufmann.
    Multi-Player Bandits Revisited.
    ALT, Lanzarote, Canari Islands, April 2018.
    [ PDF ] • [ Mobile version ] • [ Slides ] • [ Poster ] • [ arXiv ] • [ HAL ] • [ BibTeX ] • [ Code (LaTeX) ] • [ Code ]
    Presented a few times… In 2017 and 2018, I presented different versions of these slides for a SequeL seminar in Lille on December 22th, for the ALT conference in Lanzarote (Spain) on April 8th 2018, and I presented this poster for a Workshop on Multi-Armed Bandits and Learning Algorithms on May 24th 2018 in Rotterdam School of Management (Erasmus University, Netherlands), for the IETR lab "PhD Students Day" on June 15th 2018 (Vannes, France), and one last time for the Workshop Optimization and Learning on September 10th 2018 in University de Toulouse in Toulouse (France).
  4. L. Besson, E. Kaufmann & C. Moy.
    Aggregation of Multi-Armed Bandits learning algorithms for Opportunistic Spectrum Access.
    IEEE WCNC, Barcelona, Spain. April 2018.
    • [ PDF ] • [ Mobile version ] • [ Slides ] • [ HAL ] • [ BibTeX ] • [ Code (LaTeX) ] • [ Code ]
  5. R. Bonnefoi, L. Besson, C. Moy, E. Kaufmann & J. Palicot.
    Multi-Armed Bandit Learning in IoT Networks and non-stationary settings.
    CrownCom, Lisboa, Portugal. September 2017. Best Paper Award!
    [ PDF ] • [ Mobile version ] • [ Slides ] • [ Poster ] • [ arXiv ] • [ HAL ] • [ BibTeX ] • [ Code (LaTeX) ] • [ Code (MATLAB) ] • [ DOI ] • [ Proceedings ]
    Presented a few times… In 2017 I presented different versions of these slides for a SequeL seminar in Lille on September 15th, for the CrownCom conference in Lisboa on September 22th, for this research day organized by the GdR-ISIS in Paris on November 17th, and for the SCEE seminar in Rennes on November 23th.

Academic publications

  1. L. Besson, J. Fageot, M. Unser.
    A Theoretical Study Of Steerable Homogeneous Operators, And Applications.
    Research Internship Report – Master MVA. Internship with Prof.Dr. Michael Unser and Dr. Julien Fageot. BIG team at EPFL, Lausanne (Switzerland). August 2016.
    [ PDF ] • [ Slides ] • [ Code ] • [ 🏅 Rank: 1st & 🎓 Grade: 18.43/20 ]

🎓   Teaching

My wish is to become a tenured full-time teaching professor in a Preparatory School in France (CPGE), in Computer Science and/or Maths. Ideally, I will be the happiest man if I could spend the next 40 years teaching introductory Computer Science with Python, data structures and algorithmics, computer architecture etc. I like to share my passion for practical computer science and mathematics, and how both can be combined and used for research and modelisation problems, for instance for analysis of data coming from our daily life (e.g., my text messages, quotes from the Kaamelott TV show, or data about the national result for the maths agrégation exam, etc).

💻   Code

I love to program and write code and documentation , especially in Python for science, GNU Bash for desktop automation, and HTML/CSS/JS for the web. Everything I did and do is open-source and published (using Git), on my GitHub or my Bitbucket profiles.

Here are a few things I did since 2012:

  • 2018 : 🇫🇷 A clone of the code used by French government to decide the affectation between highschool students and universities (ParcoursSup), written in 🐍 Python 3. Aimed at being didactic. Documentation here (in French), and an interactive notebook here (in French). Documentation Status Build Status Binder GitHub stars GitHub watchers
  • 2018 : Gym-NES-Mario-Bros 🐍 🏋 OpenAI GYM for Nintendo NES emulator FCEUX and 1983 game Mario Bros. + Double Q Learning for mastering the game with reinforcement learning. GitHub forks GitHub stars GitHub watchers
  • 2017 : Jupyter-NBConvert-OCaml , custom Jupyter 📓 NBConvert exporter for the 🐫 OCaml language (and ocaml-jupyter kernel) GitHub stars GitHub watchers
  • 2017 : small Python 🐍 (Lempel-Ziv_Complexity) and Julia (LempelZiv.jl) libraries to efficiently compute the Lempel-Ziv complexity between two binary strings. Published on Pypi and METADATA.jl PyPI version GitHub stars GitHub stars
  • 2016 : uLogMe , self-monitoring software for GNU/Linux, with zero CPU overhead and outstanding visualizations. GitHub forks GitHub stars
  • 2013 : StrapDown.js , An awesome Javascript tool to quickly publish nice-looking webpages from raw Markdown, no server-side compilation. Light script Only 32 Kb. GitHub forks GitHub stars GitHub watchers
  • Since 2012 : My résumé 🎓, is open-source and publicly available, self hosted.