Section: Dissemination

Teaching - Supervision - Juries

Teaching

• Doctorat: Émilie Kaufmann and Odalric-Ambrym-Maillard, “Bandit algorithms I”, RLSS Summer School, Lille, 9h, July 2019

• Master: Émilie Kaufmann, “Data Mining”, 36h, M1, Université de Lille, Jan-Apr 2019

• Master: Émilie Kaufmann, “Reinforcement Learning”, 24h, M2, Ecole Centrale de Lille, Nov 2019-Jan 2020

• Master: Odalric-Ambrym Maillard, “Reinforcement Learning”, 38h equivalent TD, M2, Ecole Polytechnique, Palaiseau, Jan-Mar 2019

• Doctorat: Odalric-Ambrym Maillard, “Bandit algorithms II”, RLSS Summer School, Lille, 9h, July 2019

• Doctorat: Philippe Preux, “Reinforcement Learning”, Fall School on AI (IA2) of the GDR IA (CNRS), Lyon, 3h, Oct 2019

• Doctorat: Philippe Preux, “AI learns to act”, MOMI, Sophia-Antipolis, 1h30, Feb 2019

Supervision

• HdR: Odalric-Ambrym Maillard, Mathematics of Sequential Decision Making, Université de Lille, Feb 11, 2019

• PhD: Lilian Besson, Multi-players Bandit Algorithms for Internet of Things Networks, CentraleSupélec Rennes, Nov 20, 2019, supervisors: Christophe Moy (Université de Rennes) et Émilie Kaufmann

• PhD: Ronan Fruit, Exploration–exploitation dilemma in Reinforcement Learning under various form of prior knowledge, Université de Lille, Nov 6, 2019, supervisor: Alessandro Lazaric

• PhD: Nicolas Carrara, “Apprentissage par renforcement pour optimisation de systèmes de dialogue via l'adaptation à chaque utilisateur”, Université de Lille, Dec 18, 2019, supervisor: Oliier Pietquin

• PhD in progress: Dorian Baudry, “Efficient Exploration for Structured Bandits and Reinforcement Learning”, since Nov 2019, supervisors: É. Kaufmann, O-A. Maillard

• PhD in progress: Omar Darwiche Domingues, “Sequential Learning in Dynamic Environments”, since Oct 2018, supervisors: É. Kaufmann, M. Valko

• PhD in progress: Johan Ferret, “Explainable Reinforcement Learning via Deep Neural Networks”, since Fall 2019, supervisor: Ph. Preux, O. Pietquin

• PhD in progress: Yannis Flet-Berliac, “Deep reinforcement learning in stochastic and non stationary environments”, since Oct 2018, supervisor: Ph. Preux

• PhD in progress: Guillaume Gautier, DPPs in ML, started Oct 2016, defense scheduled in March 2020. Supervisors: R. Bardenet, M. Valko.

• PhD in progress: Jean-Bastien Grill, “Création et analyse d'algorithmes efficaces pour la prise de décision dans un environnement inconnu et incertain”, started Oct 2014, defended on Dec 19, 2019. Supervisors: R. Munos, M. Valko

• PhD in progress: Nathan Grinsztajn, “Apprentissage par renforcement pour la résolution séquentielle de problèmes d’optimisation combinatoire incertains et partiellement définis”, since Fall 2019, supervisor: Ph. Preux

• PhD in progress: Léonard Hussenot, “Adversarial reinforcement learning: attacks and robustness”, since Fall 2019, supervisor: Ph. Preux, O. Pietquin

• PhD in progress: Édouard Leurent, “Autonomous vehicle control: application of machine learning to contextualized path planning”, since Oct 2017, supervisors: O-A. Maillard, D. Effimov (Valse), W. Perruquetti (CRIStAL)

• PhD in progress: Reda Ouhamma, “Automated feature representation”, since Fall 2019, O-A. Maillard

• PhD in progress: Pierre Perrault, “Online Learning on Streaming Graphs”, since Sep 2017, supervisors: M. Valko, V. Perchet

• PhD in progress: Sarah Perrin, “Reinforcement Learning in Mean Field Games”, since Fall 2019, supervisors: O. Pietquin, R. Elie

• PhD in progress: Hassan Saber, “Structured multi-armed bandits”, since Oct 2018, Structured Multi-armed bandits, supervisor: O-A. Maillard.

• PhD in progress: Mathieu Seurin, “Multi-scale rewards in reinforcement learning”, since Oct 2017, supervisors: O. Pietquin, Ph. Preux

• PhD in progress: Julien Seznec, “Sequential Learning for Educational Systems”, since Mar 2017, supervisors: M. Valko, A. Lazaric, J. Banon

• PhD in progress: Xuedong Shang, “Adaptive methods for optimization in stochastic environments”, started Oct 2017, supervisors: É. Kaufmann, M. Valko

• PhD in progress: Florian Strub, “Reinforcement Learning for visually grounded interaction”, since Jan 2016, defense scheduled for Jan 2020, supervisors: O. Pietquin and J. Mary

• PhD in progress: Kiewan Villatel, “Deep Learning for Conversion Rate Prediction in Online Advertising”, started Oct 2017, aborted June 2019, supervisor: Ph. Preux

Juries

• Émilie Kaufmann:

  • Aristide Tossou, member of the jury, Chalmers University, Sweden, Nov 18, 2019

  • Rémi Degenne, member of the jury, Université Paris-Diderot, Dec 18, 2019

  • member of the Mathematics jury for the admission competition of ENS, section B/L

• Odalric-Ambrym Maillard:

  • Léonard Torossian, reviewer, Université Toulouse III, Dec 17, 2019.

• Philippe Preux:

  • Quentin Waymel (medical doctorate), member of the jury, Université de Lille, Jun 2019

  • Adrien Legrand, reviewer, Université de Picardie, Amiens, Nov 29, 2019

  • Erinc Merdivan, reviewer, Centrale-Supélec Metz, Dec 17, 2019

  • Nicolas Carrara, member of the jury, Université de Lille, Dec 18, 2019

• Michal Valko:

  • Aristide Tossou, opponent, Chalmers University, Sweden, Nov 18, 2019