Section: Dissemination

Teaching - Supervision - Juries

Teaching

• Master: É. Kaufmann, 2017/2018 Fall: Machine Learning, 18h eq TD, M2 Maths/Finances, Université de Lille 1

• Master: É. Kaufmann, 2016/2017 Spring: Data Mining, 36h eq TD, M1 Maths/Finances, Université de Lille 1

• Master: A. Lazaric, 2017/2018 Fall: Reinforcement Learning, 36h eqTD, M2, ENS Cachan

• Master: M. Valko, 2017/2018 Fall: Graphs in Machine Learning, 36h eqTD, M2, ENS Cachan

Supervision

• PhD in progress: Marc Abeille, Exploration-exploitation in reinforcement learning, started Sept. 2014, advisor: Remi Munos, Alessandro Lazaric

• PhD in progress: Merwan Barlier, Human-in-the loop reinforrcement learning for dialogue systems, started Oct. 2014, advisor: Olivier Pietquin

• PhD in progress: Alexandre Bérard, Deep learning for post-editing and automatic translation, started Oct. 2014, advisor: Olivier Pietquin

• PhD in progress: Lilian Besson, Bandit approach to improve Internet Of Things Communications, started Oct. 2016, advisor: Émilie Kaufmann, Christophe Moy (CentraleSupélec Rennes)

• PhD in progress: Daniele Calandriello, Efficient Sequential Learning in Structured and Constrained Environment, Inria, started Oct. 2014, advisor: Michal Valko, Alessandro Lazaric

• PhD in progress: Ronan Fruit, Exploration-exploitation in hierarchical reinforcement learning, Inria, started Dec. 2015, advisor: Daniil Ryabko, Alessandro Lazaric

• PhD in progress: Pratik Gajane, Multi-armed bandits with unconventional feedback, started Oct. 2014, defended Nov. 14th 2017, advisor: Philippe Preux

• PhD in progress: Guillaume Gautier, DPPs in ML, started Oct. 2016, advisor: Michal Valko; Rémi Bardenet

• PhD in progress: Jean-Bastien Grill, Création et analyse d'algorithmes efficaces pour la prise de décision dans un environnement inconnu et incertain, Inria/ENS Paris/Lille 1, started Oct. 2014, advisor: Rémi Munos, Michal Valko

• PhD in progress: Édouard Leurent, Autonomous vehicle control: application of machine learning to contextualized path planning, started Oct. 2017, advisor: Odalric Maillard, Philippe Preux, Denis Effimov (NON-A), Wilfrid Perruquetti (NON-A)

• PhD in progress: Sheikh Waqas Akhtar, Bandits for non-stationarity and structure, started Oct. 2017, advisor: Odalric Maillard, Daniil Ryabko.

• PhD in progress: Julien Perolat, Reinforcement learning: the multi-player case, started Oct. 2014, advisor: Olivier Pietquin

• PhD in progress: Pierre Perrault, Online Learning on Streaming Graphs, started Sep. 2017, advisor: Michal Valko; Vianney Perchet

• PhD in progress: Mathieu Seurin, Multi-scale rewards in reinforcement learning, started Oct. 2017, advisor: Olivier Pietquin, Philippe Preux

• PhD in progress: Julien Seznec, Sequential Learning for Educational Systems, started Mar. 2017, advisor: Michal Valko; Alessandro Lazaric, Jonathan Banon

• PhD in progress: Xuedong Shang, Adaptive methods for optimization in stochastic environments, started Oct. 2017, advisor: Émilie Kaufmann, Michal Valko

• PhD in progress: Florian Strub, Reinforcement Learning for visually grounded interaction, started Jan. 2016, advisors: Olivier Pietquin and Jeremie Mary

• PhD in progress: Kiewan Villatel, Deep Learning for Conversion Rate Prediction in Online Advertising, started Oct. 2017, advisor: Philippe Preux

Juries

PhD and HDR juries:

• É.  Kaufmann, Navikumar Modi, CentraleSupélec Rennes, May 2017

• A. Lazaric:

  • Stefano Paladino, Politecnico di Milano, Dec 2017

  • Micheal Castronovo, Université de Liege, March 2017

  • Raffaello Camoriano, Universitá di Genova, April 2017

  • Claire Vernade, TelecomParis Tech, October 2017

• Ph. Preux:

  • Cricia Zilda Felicio Paixao, Uniervity Uberlandia, Brasil

  • Thibault Gisselbrecht, LIP 6, UPMC, Paris

  • Pratik Gajane, CRIStAL, Lille

• M. Valko: Clément Bouttier, Université Toulouse 3 Paul Sabatier, June 2017

PhD mid-term evaluation:

• M. Valko: Thibault Liétard, Université Lille, September 2017