Université de Montréal
Deep learning has brought us incredibly accurate algorithms for vision, sound processing, language understanding and sequential decision making. Yet these algorithms are still prone to failure in unforeseen situations. As a PhD student at MILA , my goal is to understand what can be learned reliably (structured prediction theory), and how to learn these efficiently (optimization and games). My supervisor is Simon Lacoste-Julien.
Short bio: I am one of many Paris suburbians. I moved around from Meudon, to Versailles (preparatory class at Lycée Hoche), to Palaiseau where I studied at Ecole Polytechnique (X2013). I graduated with an engineering degree and a Master of Science in maths and machine learning (M2 MVA) in 2018. Full story in my resume.
Google Scholar profile: for my list of publications.
SDCA4CRF : During the year 2017 I worked on an optimization algorithm for a structured prediction model called CRF.
bitstring-knitting: a visual inspection of distances applied to bit strings.
Search Engine Optimization: Gabriel Huang
I enjoy climbing, hiking, slacklining, acroyoga, meditation and all kind of playful activities offered by the hippie city that is Montréal.