Pierre C. Bellec

Department of Statistics & Biostatistics, Rutgers University.

I am an Assistant Professor of statistics at Rugers, the State University of New Jersey. I obtained my PhD in 2016 from ENSAE ParisTech, where I was fortunate to have Alexandre Tsybakov as my PhD advisor. My research interests include aggregation of estimators, shape restricted regression, confidence sets, high-dimensional statistics and concentration inequalities.


2016: PhD, ENSAE ParisTech, France.
2012: Part III (MASt), University of Cambridge, UK.
2011: Diplôme d'Ingénieur, Ecole Polytechnique, France.

Preprint and submitted articles

De-biasing the Lasso with degrees-of-freedom adjustment. Pierre C Bellec and Cun-Hui Zhang.
arXiv:1902.08885, 2019.
The noise barrier and the large signal bias of the Lasso and other convex estimators. Pierre C Bellec.
arXiv:1804.01230, 2018.
Second order Stein: SURE for SURE and other applications in high-dimensional inference. Pierre C Bellec and Cun-Hui Zhang.
arXiv:1804.01230, 2018.
Optimistic lower bounds for convex regularized least-squares. Pierre C Bellec.
arXiv:1703.01332, 2017.
Adaptive confidence sets in shape restricted regression. Pierre C. Bellec.
Technical report. ArXiv:1601.05766, 2016.
Concentration of quadratic forms under a Bernstein moment assumption. Pierre C. Bellec.
Technical report. Arxiv:1901.08726, 2014.

Journal articles

Optimal bounds for aggregation of affine estimators. Pierre C. Bellec.
Ann. Statist., 46(1):30–59, 02 2018.
Sharp oracle inequalities for Least Squares estimators in shape restricted regression. Pierre C. Bellec.
Ann. Statist., 46(2):745–780, 2018.
On the prediction loss of the lasso in the partially labeled setting. Pierre C. Bellec, Arnak S. Dalalyan, Edwin Grappin, and Quentin Paris.
Electron. J. Statist., 12(2):3443–3472, 2018.
Slope meets Lasso: Improved oracle bounds and optimality. Pierre C. Bellec, Guillaume Lecué, and Alexandre B. Tsybakov.
Ann. Statist., 46(6B):3603–3642, 2018.
Localized Gaussian width of M-convex hulls with applications to Lasso and convex aggregation. Pierre C Bellec.
Bernoulli, to appear, 2017.
Optimal exponential bounds for aggregation of density estimators. Pierre C. Bellec.
Bernoulli, 23(1):219–248, 2017.
Bounds on the prediction error of penalized least squares estimators with convex penalty. Pierre C Bellec and Alexandre B Tsybakov. In
Modern Problems of Stochastic Analysis and Statistics, Selected Contributions In Honor of Valentin Konakov. Springer, 2017.
Towards the study of least squares estimators with convex penalty. Pierre C Bellec, Guillaume Lecué, and Alexandre B Tsybakov. In
Seminaire et Congres, to appear, number 39. Societe mathematique de France, 2017.
A sharp oracle inequality for Graph-Slope. Pierre C. Bellec, Joseph Salmon, and Samuel Vaiter.
Electron. J. Statist., 11(2):4851–4870, 2017.
Aggregation of supports along the Lasso path. Pierre C. Bellec.
Accepted at Conference On Learning Theory (COLT) 2016, 2016.
Sharp Oracle Bounds for Monotone and Convex Regression Through Aggregation. Pierre C. Bellec and Alexandre B. Tsybakov.
Journal of Machine Learning Research, 16:1879–1892, 2015.

Awards and Grants

Past and scheduled talks:

Reach me

Department of Statistics & Biostatistics
Rutgers, The State University of New Jersey
501 Hill Center, Busch Campus
110 Frelinghuysen Road
Piscataway, NJ 08854