Big Data and Artificial Intelligence / PERSYVAL-Minalogic Breakfasts

While Artificial Intelligence solutions are not new, they have experienced a real boom in recent years due to the emergence of Big Data, resulting in the availability of massive and heterogeneous data of all kinds, as well as increasingly powerful machine learning algorithms to exploit them thanks to computing and mathematical progress.

The objective of this meeting is to provide keys to better understand the various facets of Big Data and the main Artificial Intelligence approaches, and to better connect them with specific application needs depending on the volume and type of data produced or available. 

Program and presentations

• 08:15-08:30: Welcome
• 08:30-09:00: Introductory presentation
  Overview of Main Artificial Intelligence Approaches Related to Big Data
  Marie-Christine Rousset, Université Grenoble Alpes and Institut Universitaire de France, Laboratoire d'Informatique de Grenoble
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• 09:00-10:00: Specialized Presentations
  • Some Applications in Deep Learning
    Laurent Besacier, Université Grenoble Alpes, Laboratoire d'Informatique de Grenoble
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    In recent years, methods based on deep learning have proven to be very effective for certain difficult artificial intelligence tasks: machine translation, speech transcription, image classification, image captioning. This presentation will introduce the main principles of this booming field, as well as some "success stories" in the application areas mentioned below.
  • Statistical Learning: Principles and Focus on Biomedical Applications
    Adeline Leclercq Samson, Université Grenoble Alpes, Jean Kuntzmann Laboratory
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    Statistical learning is a rapidly growing field that proves to be a powerful decision-making tool in numerous areas. This presentation will cover the core principles along with examples of biomedical applications.
• 10:00-10:30: Discussion Session
  Presentation by Laurence Pierre: Foundations of a Corporate/University Collaboration
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