S. A. van de Geer

activity

20152024

most citedConfidence regions for high-dimensional generalized linear models under sparsity

16 citations · 17 across the 5 of their papers we have counts for

collaborators

13 papers

math.ST2024

Entropy bounds for the absolute convex hull of tensors

Sara van de Geer

We derive entropy bounds for the absolute convex hull of vectors $X = (x_{1}, \dots, x_{p}) \in R^{n \times p}$ in $R^{n}$ and apply this to the case where $X$ is the…

math.ST2023

Finite sample rates for logistic regression with small noise or few samples

Felix Kuchelmeister, Sara van de Geer

The logistic regression estimator is known to inflate the magnitude of its coefficients if the sample size $n$ is small, the dimension $p$ is (moderately) large or the signal-to-no…

math.ST2021

AdaBoost and robust one-bit compressed sensing

Geoffrey Chinot, Felix Kuchelmeister, Matthias Löffler +1

This paper studies binary classification in robust one-bit compressed sensing with adversarial errors. It is assumed that the model is overparameterized and that the parameter of i…

math.ST2017

On the efficiency of the de-biased Lasso

Sara van de Geer

We consider the high-dimensional linear regression model $Y = X β^{0} + ε$ with Gaussian noise $ε$ and Gaussian random design $X$ . We assume that $Σ := E X^{T} X / n$ is non-singular an…

math.ST2017

Asymptotic Confidence Regions for High-dimensional Structured Sparsity

Benjamin Stucky, Sara van de Geer

In the setting of high-dimensional linear regression models, we propose two frameworks for constructing pointwise and group confidence sets for penalized estimators which incorpora…

math.ST2017★ 1 cited

Some exercises with the Lasso and its compatibility constant

Sara van de Geer

We consider the Lasso for a noiseless experiment where one has observations $X β^{0}$ and uses the penalized version of basis pursuit. We compute for some special designs the compati…