102 citations · 352 across the 15 of their papers we have counts for
16 papers
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…
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…
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…
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…
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…
Connection graph Laplacian methods can be made robust to noise
Noureddine El Karoui, Hau-tieng Wu
Recently, several data analytic techniques based on connection graph laplacian (CGL) ideas have appeared in the literature. At this point, the properties of these methods are start…
Kernel Density Estimation with Berkson Error
James P. Long, Noureddine El Karoui, John A. Rice
Given a sample from , we construct kernel density estimators for , the convolution of with a known error density . This problem is known as d…
Asymptotic behavior of unregularized and ridge-regularized high-dimensional robust regression estimators : rigorous results
Noureddine El Karoui
We study the behavior of high-dimensional robust regression estimators in the asymptotic regime where tends to a finite non-zero limit. More specifically, we study ridge-regu…
Graph connection Laplacian and random matrices with random blocks
Noureddine El Karoui, Hau-tieng Wu
Graph connection Laplacian (GCL) is a modern data analysis technique that is starting to be applied for the analysis of high dimensional and massive datasets. Motivated by this tec…
A Stochastic Smoothing Algorithm for Semidefinite Programming
Alexandre d'Aspremont, Noureddine El Karoui
We use a rank one Gaussian perturbation to derive a smooth stochastic approximation of the maximum eigenvalue function. We then combine this smoothing result with an optimal smooth…
Optimizing Automated Classification of Periodic Variable Stars in New Synoptic Surveys
James P. Long, Noureddine El Karoui, John A. Rice +2
Efficient and automated classification of periodic variable stars is becoming increasingly important as the scale of astronomical surveys grows. Several recent papers have used met…
Performance-based regularization in mean-CVaR portfolio optimization
Noureddine El Karoui, Andrew E. B. Lim, Gah-Yi Vahn
We introduce performance-based regularization (PBR), a new approach to addressing estimation risk in data-driven optimization, to mean-CVaR portfolio optimization. We assume the av…
Weak Recovery Conditions from Graph Partitioning Bounds and Order Statistics
Alexandre d'Aspremont, Noureddine El Karoui
We study a weaker formulation of the nullspace property which guarantees recovery of sparse signals from linear measurements by l_1 minimization. We require this condition to hold…
The spectrum of kernel random matrices
Noureddine El Karoui
We place ourselves in the setting of high-dimensional statistical inference where the number of variables in a dataset of interest is of the same order of magnitude as the numb…
Concentration of measure and spectra of random matrices: Applications to correlation matrices, elliptical distributions and beyond
Noureddine El Karoui
We place ourselves in the setting of high-dimensional statistical inference, where the number of variables in a data set of interest is of the same order of magnitude as the nu…
Second order accurate distributed eigenvector computation for extremely large matrices
Noureddine El Karoui, Alexandre d'Aspremont
We propose a second-order accurate method to estimate the eigenvectors of extremely large matrices thereby addressing a problem of relevance to statisticians working in the analysi…