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20072025
most citedLeast squares after model selection in high-dimensional sparse models

630 citations · 1.9k across the 32 of their papers we have counts for

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19 papers · 1 filter

math.ST2024

Adversarial Estimation of Binary Configuration Probabilities under Sparse Dependence

Alexandre Belloni, Yan Chen, Matthew Harding

We consider the problem of estimating binary configuration probabilities, which is common in operations management applications, including product bundling, advertising, etc. Exist…

math.ST2024

Anti-Concentration Inequalities for the Difference of Maxima of Gaussian Random Vectors

Alexandre Belloni, Ethan X. Fang, Shuting Shen

We derive novel anti-concentration bounds for the difference between the maximal values of two Gaussian random vectors across various settings. Our bounds are dimension-free, scali…

math.ST2018★ 2 cited

A high dimensional Central Limit Theorem for martingales, with applications to context tree models

Alexandre Belloni, Roberto I. Oliveira

We establish a central limit theorem for (a sequence of) multivariate martingales which dimension potentially grows with the length of the martingale. A consequence of the resu…

math.ST2018★ 10 cited

Subvector Inference in Partially Identified Models with Many Moment Inequalities

Alexandre Belloni, Federico Bugni, Victor Chernozhukov

This paper considers inference for a function of a parameter vector in a partially identified model with many moment inequalities. This framework allows the number of moment condit…

math.ST2018★ 16 cited

High-Dimensional Econometrics and Regularized GMM

Alexandre Belloni, Victor Chernozhukov, Denis Chetverikov +2

This chapter presents key concepts and theoretical results for analyzing estimation and inference in high-dimensional models. High-dimensional models are characterized by having a…

math.ST2017★ 3 cited

Confidence Bands for Coefficients in High Dimensional Linear Models with Error-in-variables

Alexandre Belloni, Victor Chernozhukov, Abhishek Kaul

We study high-dimensional linear models with error-in-variables. Such models are motivated by various applications in econometrics, finance and genetics. These models are challengi…