P. Bellec

发表

Sharp oracle inequalities for Least Squares estimators in shape restricted regression

P. Bellec, 2015, 1510.08029.

Slope meets Lasso: Improved oracle bounds and optimality

A. Tsybakov, G. Lecu'e, P. Bellec, 2016, The Annals of Statistics.

On the prediction loss of the lasso in the partially labeled setting

A. Dalalyan, P. Bellec, Q. Paris, 2016, 1606.06179.

A sharp oracle inequality for Graph-Slope

P. Bellec, J. Salmon, Samuel Vaiter, 2017, 1706.06977.

The noise barrier and the large signal bias of the Lasso and other convex estimators

P. Bellec, 2018, 1804.01230.

Mutations associated with neuropsychiatric conditions delineate functional brain connectivity dimensions contributing to autism and schizophrenia

Alan C. Evans, T. Bourgeron, P. Quirion, 2020, Nature Communications.

Optimal exponential bounds for aggregation of density estimators

P. Bellec, 2014, 1405.3907.

Bounds on the Prediction Error of Penalized Least Squares Estimators with Convex Penalty

Pierre C. Bellec, Alexandre B. Tsybakov, A. Tsybakov, 2016, 1609.06675.

Towards the study of least squares Estimators with convex penalty

A. Tsybakov, G. Lecu'e, P. Bellec, 2017, 1701.09120.

Functional Connectivity of Successful Picture-Naming: Age-Specific Organization and the Effect of Engaging in Stimulating Activities

P. Bellec, Y. Joanette, S. Brambati, 2020, Frontiers in Aging Neuroscience.

Poincaré inequalities and de-biasing arbitrary convex regularizers when p / n → γ

Cun-Hui Zhang, P. Bellec, 2019 .

Second order Poincaré inequalities and de-biasing arbitrary convex regularizers when $p/n \to γ$

Pierre C. Bellec, Cun-Hui Zhang, Cun-Hui Zhang, 2019 .

1 2 O ct 2 01 9 First order expansion of convex regularized estimators

P. Bellec, 2019 .

Functional neuroanatomy associated with the expression of distinct movement kinematics in motor sequence learning

P. Peigneux, P. Maquet, J. Doyon, 2011, Neuroscience.

Submitted to the Annals of Statistics SLOPE MEETS LASSO : IMPROVED ORACLE BOUNDS AND OPTIMALITY By

A. Tsybakov, Guillaume Lecué, P. Bellec, 2017 .

Sharp oracle inequalities in aggregation and shape restricted regression

P. Bellec, 2016 .

Noise Covariance Estimation in Multi-Task High-dimensional Linear Models

P. Bellec, Kai Tan, Gabriel Romon, 2022, 2206.07256.

On the open-source landscape of PLOS Computational Biology

J. Poline, P. Bellec, N. Stikov, 2021, PLoS Comput. Biol..

ST ] 3 1 M ay 2 01 6 Aggregation of supports along the Lasso path

P. Bellec, 2018 .

Noise Covariance Estimation in Multi-Task High-dimensional Linear Models

P. Bellec, Kai Tan, Gabriel Romon, 2022, 2206.07256.

Observable adjustments in single-index models for regularized M-estimators

P. Bellec, 2022, 2204.06990.

Optimal bounds for aggregation of affine estimators

P. Bellec, 2014, 1410.0346.

Optimistic lower bounds for convex regularized least-squares

P. Bellec, 2017, 1703.01332.

An open science resource for establishing reliability and reproducibility in functional connectomics

Bing Chen, Tianzi Jiang, Zhe Zhang, 2014, Scientific Data.

Chi-square and normal inference in high-dimensional multi-task regression

Pierre C. Bellec, Gabriel Romon, P. Bellec, 2021, 2107.07828.

Representational learning of brain responses in executive function and higher-order cognition using deep graph convolutions

A. Dagher, P. Bellec, Nicolas Farrugia, 2021, bioRxiv.

Cerebral functional networks during sleep in young and older individuals

G. Vandewalle, P. Maquet, J. Doyon, 2021, Scientific Reports.

Dissecting autism and schizophrenia through neuroimaging genomics

P. Thompson, M. Chakravarty, P. Bellec, 2021, Brain : a journal of neurology.

Asymptotic normality of robust M-estimators with convex penalty

Cun-Hui Zhang, Pierre C Bellec, Yiwei Shen, 2021, Electronic Journal of Statistics.

The Three Terms Task - an open benchmark to compare human and artificial semantic representations

P. Bellec, M. Hebart, V. Borghesani, 2023, Scientific Data.

The Cost-free Nature of Optimally Tuning Tikhonov Regularizers and Other Ordered Smoothers

Dana Yang, Pierre C Bellec, P. Bellec, 2019, ICML.

De-biasing the lasso with degrees-of-freedom adjustment

Pierre C. Bellec, Cun-Hui Zhang, Cun-Hui Zhang, 2019, Bernoulli.

Debiasing convex regularized estimators and interval estimation in linear models

Cun-Hui Zhang, P. Bellec, 2019, The Annals of Statistics.

Out-of-sample error estimate for robust M-estimators with convex penalty

P. Bellec, 2020, 2008.11840.

SOME METHODS FOR STATISTICAL INFERENCE USING HIGH-DIMENSIONAL LINEAR MODELS

W. Bajwa, P. Bellec, E. Soljanin, 2019 .

First order expansion of convex regularized estimators

Pierre C. Bellec, Arun Kumar Kuchibhotla, Arun K. Kuchibhotla, 2019, NeurIPS.

Asymptotic normality and confidence intervals for derivatives of 2-layers neural network in the random features model

Pierre C. Bellec, Yiwei Shen, P. Bellec, 2020, NeurIPS.

Second-order Stein: SURE for SURE and other applications in high-dimensional inference

Cun-Hui Zhang, Pierre C Bellec, Cun-Hui Zhang, 2018, The Annals of Statistics.

Concentration of quadratic forms under a Bernstein moment assumption

Pierre C Bellec, P. Bellec, 2019, 1901.08736.

Adaptive confidence sets in shape restricted regression

Pierre C. Bellec, P. Bellec, 2016, Bernoulli.

Sharp oracle bounds for monotone and convex regression through aggregation

Pierre C. Bellec, Alexandre B. Tsybakov, A. Tsybakov, 2015, J. Mach. Learn. Res..

Deep learning models of cognitive processes constrained by human brain connectomes

P. Bellec, Nicolas Farrugia, Yu Zhang, 2021, bioRxiv.

Localized Gaussian width of $M$-convex hulls with applications to Lasso and convex aggregation

Pierre C Bellec, P. Bellec, 2017, Bernoulli.

Generative Adversarial Neuroevolution for Control Behaviour Imitation

P. Bellec, Maximilien Le Clei, 2023, GECCO Companion.

Aggregation of supports along the Lasso path

Pierre C. Bellec, P. Bellec, 2016, COLT.

Derivatives and residual distribution of regularized M-estimators with application to adaptive tuning

Pierre C Bellec, Yiwei Shen, Yi Shen, 2021, COLT.