103 citations · 107 across the 6 of their papers we have counts for
8 papers
Uncertainty quantification for iterative algorithms in linear models with application to early stopping
Pierre C. Bellec, Kai Tan
This paper investigates the iterates $\hbb^1,\dots,\hbb^T$ obtained from iterative algorithms in high-dimensional linear regression problems, in the regime where the feature dimens…
Scaling up ridge regression for brain encoding in a massive individual fMRI dataset
Sana Ahmadi, Pierre Bellec, Tristan Glatard
Brain encoding with neuroimaging data is an established analysis aimed at predicting human brain activity directly from complex stimuli features such as movie frames. Typically, th…
Multinomial Logistic Regression: Asymptotic Normality on Null Covariates in High-Dimensions
Kai Tan, Pierre C. Bellec
This paper investigates the asymptotic distribution of the maximum-likelihood estimate (MLE) in multinomial logistic models in the high-dimensional regime where dimension and sampl…
Generative Adversarial Neuroevolution for Control Behaviour Imitation
Maximilien Le Clei, Pierre Bellec
There is a recent surge in interest for imitation learning, with large human video-game and robotic manipulation datasets being used to train agents on very complex tasks. While de…
Neuroevolution of Recurrent Architectures on Control Tasks
Maximilien Le Clei, Pierre Bellec
Modern artificial intelligence works typically train the parameters of fixed-sized deep neural networks using gradient-based optimization techniques. Simple evolutionary algorithms…
Bounds on the prediction error of penalized least squares estimators with convex penalty
Pierre C. Bellec, Alexandre B. Tsybakov
This paper considers the penalized least squares estimator with arbitrary convex penalty. When the observation noise is Gaussian, we show that the prediction error is a subgaussian…