Students
PhD students
Camille-Sovanneary Gauthier (2019 - 2022) homepage, LinkedIn
Title: Learning to Rank in a bandit setting
Funding: Louis Vuitton (Cifre)
Co-advisors: Élisa Fromont (50%) and Romaric Gaudel (50%)
Advisors at Louis Vuitton: Bruno Guilbot and Éliot Barril
Anh Duong NGUYEN (2018 - 2019)
Title: Compression Based Pattern Mining
‘Direction’: Alexandre Termier
Co-advisors: Romaric Gaudel (50%), Peggy Cellier (25%), and Alexandre Termier (25%)
Ended after 1 year
Frédéric Guillou (2013 - 2016), Senior LinkedIn
Title: Sequential Recommender Systems
‘Direction’: Philippe Preux
Co-advisors: Jérémie Mary (50%), Romaric Gaudel (50%)
Undergraduate/graduate internships
2021 : Matthieu Rodet (M1, 1 day a week for the whole year) Unimodal Bandit for Learning to Match (co-advised with É. Fromont)
2020 : Maxime Heuillet (M2 internship, 1 month) A neural network approach to privacy preserving multi-engagement prediction on Twitter
2020 : Aser Boammani Lompo (M1 internship, 2 months) Unimodal bandit for list-wise recommendation
2020 : Alex Georget (M1 internship, 3 months) Unimodal bandit for list-wise recommendation
2020 : Théo Velletaz (M1 internship, 3 months) Interpretation of continuous models (co-advised with L. Galárraga)
2019 : Vaishnavi Barghava (Bachelor internship, 4 months) Automatic Neighborhood Design for Localized Model-interpretation (co-adivsed with L. Galárraga)
2018 : Grégoire Pacreau (L3 internship, 1.5 months) non-crude MDL based Pattern Mining (co-advised with A. Termier et P. Cellier)
2018 : Erwan Bourran (M2 internship) MCTS approach for MDL based Pattern Mining (co- advised with A. Termier et P. Cellier)
2017-2018 : Hippolyte Bourel, Nathan Koskas and Jimmy Petit (M1, 1 day a week for the whole year) Review of Time Series prediction models (co-advised with É. Fromont et L. Rozé)
2017 : Leonardo Cella (post-M2, 1 week a month for 4 months) Bandit based Recommender Systems
2016 : Rida Darmal and Zakaria Hadjadji (M1, 1 day a week for a semester) Recommender Systems with meta-data
2016 : Pierrick Deshayes and Amine El-Mabkhout, (M1, 1 day a week for a semester) rank adaptation for Sequential Recommender Systems
2016 : Mehdi Abbana Bennani (M1 internship, 3 months) Neural Network based Recommender Systems
2014-2015 : Erivan Cogez (L3, half a day a week for a semester) Sequential Recommender Systems
2014 : Mathias Sablé Meyer (L3 internship, 1.5 months) Sequential Recommender Systems
2012 : Florian Gas (M2, half a day a week for a semester) Extreme Values Theory for Extremely Multi-Armed Bandits