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HAL (département Données et Apprentissage Artificiel)
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Équipe : MLIA - Machine Learning and Information Access

Responsable : Patrick Gallinari Site Jussieu 26-00/521

Brève présentation

The central topic of the team is statistical machine learning with an emphasis on algorithmic aspects and on application domains involving semantic data analysis. The mains axes of our fundamental research contributions are:

Theoretical and algorithmic contributions are often developed together with practical applications in selected domains at MLIA:


MLIA is strongly involved in the Data Science Master cursus launched in 2014, with 9 courses taught by team members, L. Denoyer is co-responsible for this cursus.

National/ International Collaborations

MLIA has developed close international cooperation with China, Brazil, Italy, Singapour involving co-publications and researcher exchanges. It participates to joint projects with different countries (Greece, Belgium, Italy, Germany, Canada, Saudi Arabia). In France MLIA has been collaborating with teams in Grenoble, Lille, St Etienne, Marseille. MLIA is engaged in 2 international and 3 national academic projects.

Cooperation with Industrial partners

We have been engaged together with the LFI team in a close cooperation with Thales embodied in a joint lab. for 6 years now. MLIA has several close cooperation with industrial partners, mostly through joint national or EU projects. MLIA participates to 1 international and 5 national R&D projects. On September 2016 MLIA was selected together with 22 European teams, as a recipient of the Facebook partnership program for providing academic labs GPU servers for promoting AI and Deep Learning.

Statistical machine Learning, Neural Networks, Deep Learning, Reinforcement Learning, Vision, Natural Language Processing and Information Retrieval
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