activity
20162026
most citedThe bootstrap, covariance matrices and PCA in moderate and high-dimensions

12 citations · 23 across the 4 of their papers we have counts for

collaborators

5 papers

stat.ML2026

Distillation of Synthetic Data for Time Series Foundation Models

Niloy Biswas, Noureddine El Karoui

Time series foundation models (TSFMs) are increasingly pre-trained on synthetically generated time series trajectories, where the data generating process is known. Current pre-trai…

stat.ML2020

Achieving Fairness via Post-Processing in Web-Scale Recommender Systems

Preetam Nandy, Cyrus Diciccio, Divya Venugopalan +3

Building fair recommender systems is a challenging and crucial area of study due to its immense impact on society. We extended the definitions of two commonly accepted notions of f…

math.ST2016

Asymptotics For High Dimensional Regression M-Estimates: Fixed Design Results

Lihua Lei, Peter J. Bickel, Noureddine El Karoui

We investigate the asymptotic distributions of coordinates of regression M-estimates in the moderate regime, where the number of covariates grows proportionally with the…

stat.ME2016★ 12 cited

The bootstrap, covariance matrices and PCA in moderate and high-dimensions

Noureddine El Karoui, Elizabeth Purdom

We consider the properties of the bootstrap as a tool for inference concerning the eigenvalues of a sample covariance matrix computed from an data matrix . We focus…

stat.ME2016★ 11 cited

Can we trust the bootstrap in high-dimension?

Noureddine El Karoui, Elizabeth Purdom

We consider the performance of the bootstrap in high-dimensions for the setting of linear regression, where but is not close to zero. We consider ordinary least-squares…