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From robot motion in natural environments to many language translation, the machine learning and other bio-inspired techniques allow now solving problems once due to intelligent beings.
Are the assumptions on the statistical nature of learning useful to understand how brain works?
Two presentations as a basis for further discussions:
Charles-Pierre Astolfi: An introduction to machine learning.
This presentation will give some insights about machine learning: its capabilities, its boundaries, its applications, and some theory behind all of that.
I will give an overview of what it is useful for, what are the big challenges, and make a small demo on a real-world example.
Catherine Wacongne: The bayesian brain.
This presentation will give an introduction to bayesian theory; and explore why this powerful framework is getting one of the most popular theories of how the brain perceive and integrates information to make decisions.
when: starting 7PM July 11th
where: http://www.cri-paris.org/en/accueil-cri/informations-pratiques/
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