Section: Dissemination

Teaching - Supervision - Juries

Teaching

• Master: E. Kaufmann, Spring 2018, Data Mining, M1 Maths/Finances, Université de Lille (36 hours)

• Master: E. Kaufmann, Spring 2018, Machine Learning, M2 Maths/Finances, Université de Lille (18 hours)

• Master: M. Valko, 2018/2019: Graphs in Machine Learning, 36h eqTD, M2, ENS Cachan

• Master: O. Maillard, Spring 2018: Sequential Learning course, parcours DAD, 30h eqTD, Ecole Centrale Lille.

• Master: O. Maillard, January 2018: Sequential Learning tutorial, Technicolor, 6h eqTD, Rennes

Supervision

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

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

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

• 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

• PhD in progress: Yannis Flet-Berliac, start Oct. 2018

• PhD in progress: Hassan Saber, start Oct. 2018, Structured Multi-armed bandits, advisor: Odalric Maillard, Philippe Preux.

• PhD in progress: Omar Darwiche, start Oct. 2018, Sequential Learning in Dynamic Environments, advisor: Émilie Kaufmann, Michal Valko

Juries

PhD and HDR juries:

• É. Kaufmann:

  • Stefan Magureanu, KTH Stockholm, February 20th, 2018

  • Valentin Reis, LIG, Grenoble, September 28th, 2018

  • Maryam Aziz, Northestearn University (Boston), December 6th, 2018

• O. Maillard: Stefan Magureanu, February 20th, 2018

• Ph. Preux:

  • Saeed Varasteh Yazdi, LIG, Grenoble

  • Fabien Vilar, Marseille

  • Merwan Barlier, Lille

• M. Valko:

  • Pierre Ménard, Université Toulouse 3 Paul Sabatier, June 2018, Sur la notion d'optimalité dans les problèmes de bandits stochastiques. Reviewer

  • Mariana Vargas Vieyra, Université Lille, September 2017, Adaptive graph learning with application to natural language processing. Ph.D. mid-term evaluation reviewer