Lucas Maystre

Hi, I'm Lucas, a PhD candidate in Computer Science at EPFL. My research interests revolve around machine learning and its applications to recommender systems.

My thesis is about learning preferences from comparisons. I'm studying this problem from a statistical and algorithmic perspective. Since 2016, my work is supported by a Google PhD fellowship.

Papers & resources

Below is a list of recent papers. I also maintain a Google Scholar page. For more context on the projects behind these publications, check out the projects page.

The Player Kernel
L. Maystre, Victor Kristof, Antonio J. González Ferrer, Matthias Grossglauser, Sept. 2016, preprint, arXiv:1609.01176 [cs.LG].

Fast and Accurate Inference of Plackett–Luce Models
L. Maystre, M. Grossglauser, NIPS, 2015.

Robust Active Ranking from Sparse Noisy Comparisons
L. Maystre, M. Grossglauser, Feb. 2015, preprint, arXiv:1502.05556 [stat.ML].

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Mitigating Epidemics through Mobile Micro-measures
M. Kafsi, E. Kazemi, L. Maystre, L. Yartseva, M. Grossglauser, P. Thiran, Feb. 2013, preprint, arXiv:1307.2084 [cs.SI].

Music Recommendation to Groups
L. Maystre, M.Sc. thesis, EPFL, Switzerland, 2012.

I aim to share all the code and data that is involved in my research. Some of it is available on GitHub. If you cannot find something, please contact me.