Catégorie
The Palaisien Seminar
Date de tri

« Le Séminaire Palaisien » | Solenne Gaucher and Nicolas Vayatis on machine learning and statistics

Bandeau image
palaisien

« Le Séminaire Palaisien » | Solenne Gaucher and Nicolas Vayatis on machine learning and statistics

Lieu de l'événement
URL : https://bluejeans.com/9352872428/9913
Date de l'événement (intitulé)
6 April 2021 - 16.00
Chapo
Le Séminaire Palaisien gathers, every first Tuesday of the month, the vast research community of Saclay around statistics and machine learning.
Contenu
Corps de texte

Each seminar session is divided into 2 scientific presentations of 40 minutes each: 30 minutes of presentation and 10 minutes of questions.

Solenne Gaucher (Université Paris-Saclay) and Nicolas Vayatis (ENS Paris-Saclay) will lead the session of April 2021.

Nom de l'accordéon
« Continuum-armed bandits: from the classical setting to the finite setting » - Solenne Gaucher
Texte dans l'accordéon

Bandits are used to model the following sequential decision problem : at each time step, an agent takes an action and receives a reward drawn i.i.d. from a distribution depending on the action she has selected. Her aim is to maximize her cumulative reward. In this talk, we start by introducing the continuum-armed bandit, and present classical algorithms and results. In this setting, actions are indexed by covariates in a continuous set. The expected reward for taking an action is modeled as an (unknown) function of the covariate describing this action. In a second time, we focus on the finite continuum-armed bandit setting, where the set of actions is finite, and each action can only be taken once.

Nom de l'accordéon
« Can Machine Learning predict Human Behavior? » - Nicolas Vayatis
Texte dans l'accordéon

Behavioral neurosciences are about to undergo a major shift due to a) the dissemination of wearable and ambient sensors in routine clinical assessment or in complex Human-Machine interaction, b) the progressive abandonment of animal experimentation. This raises several issues in terms of observational data, but also questions how Machine Learning techniques may contribute to the data-driven quantification and prediction of Human behavior. In this talk, I will introduce the topic of Machine Learning applications to behavioral neurosciences. I will also give an overview of recent works and questions for the future of Machine Learning research in this field.