5 citations · 5 across the 5 of their papers we have counts for
5 papers
Spiking Neural Models for Decision-Making Tasks with Learning
Sophie Jaffard, Giulia Mezzadri, Patricia Reynaud-Bouret +1
In cognition, response times and choices in decision-making tasks are commonly modeled using Drift Diffusion Models (DDMs), which describe the accumulation of evidence for a decisi…
Model selection for behavioral learning data and applications to contextual bandits
Julien Aubert, Louis Köhler, Luc Lehéricy +2
Learning for animals or humans is the process that leads to behaviors better adapted to the environment. This process highly depends on the individual that learns and is usually ob…
General oracle inequalities for a penalized log-likelihood criterion based on non-stationary data
Julien Aubert, Luc Lehéricy, Patricia Reynaud-Bouret
We prove oracle inequalities for a penalized log-likelihood criterion that hold even if the data are not independent and not stationary, based on a martingale approach. The assumpt…
CHANI: Correlation-based Hawkes Aggregation of Neurons with bio-Inspiration
Sophie Jaffard, Samuel Vaiter, Patricia Reynaud-Bouret
The present work aims at proving mathematically that a neural network inspired by biology can learn a classification task thanks to local transformations only. In this purpose, we…
Optimal kernel selection for density estimation
M Lerasle, N Magalhães, P Reynaud-Bouret
We provide new general kernel selection rules thanks to penalized least-squares criteria. We derive optimal oracle inequalities using adequate concentration tools. We also investig…