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There are 15 Results with the keyword : "machine learning"

Jan Ramon - © Inria / Photo C. Morel

European Research Council 2016

Jan Ramon: “machine learning, at the heart of research”

8/11/2016

Jan Ramon, a researcher in Magnet project-team at the Inria Research Centre in Lille, has just obtained an ERC (European Research Council) Proof of Concept Grant. His goal is to build a bridge between pure research and the development of concrete data processing applications.

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Associate teams

LEGO: teaching natural language to machines

Sophie Timsit - 6/06/2018

Teaching machines to analyze language and words in a large volume of data in order to extract information and perform tasks... This is the objective of the LEGO associate team’s research: “LEarning GOod representations for automatic natural language processing.” Begun in January 2016 for a period of 3 years, LEGO brings together the Magnet project team* and the University of Southern California. It is a partnership which will soon come to an end but which promises further advances.

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Event

EWRL 14

1/10/2018 to 3/10/2018

The  14th European workshop on Reinforcement Learning will be organised by SequeL Team. This workshop will be held from 1st to 3rd october at ENSAM in Lille.

Place : ENSAM, 8 boulevard Louis XIV 59800 Lille

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Artificial Intelligence

Artificial intelligence: the Lille center at the cutting edge of machine learning

11/07/2018

Of the 16 project teams at the Inria Lille - Nord Europe center, nine have research projects linked to artificial intelligence, either directly or indirectly. Here is an overview of the Inria Lille forces in AI.

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Home > Centre > Lille > News > Le centre de Lille à la pointe de l’apprentissage automatique

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Artificial intelligence

When machines learn to forget

22/06/2018

The work of Daniele Calandriello, a doctoral candidate on the Project Sequel team at the Inria Lille - Nord Europe research center, has just received an award from the French Association for Artificial Intelligence (AFIA). He has developed a method by which machines retain only the essential elements of very big datasets in order to make them more independent.

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