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Sara van de Geer

Sara van de Geer

D-Index & Metrics

Mathematics

D-Index
43
Citations
20230
World Ranking
1640
National Ranking
32

Research.com Recognitions

  • 2020 - Member of Academia Europaea
  • 2016 - Wald Memorial Lecturer

Overview

Sara van de Geer is affiliated with ETH Zurich in Switzerland, contributing extensively to the fields of mathematics, computer science, and engineering. Their work spans multiple subfields such as statistics and probability, computational mechanics, artificial intelligence, and computational mathematics.

Their research primarily addresses topics including statistical methods and inference, sparse and compressive sensing techniques, machine learning and algorithms, probabilistic and robust engineering design, tensor decomposition and applications, mathematical approximation and integration, and neural networks and applications.

Frequent coauthors in their research collaborations include Geoffrey Chinot, Matthias Löffler, Felix Kuchelmeister, Francesco Ortelli, and Peter Hinz.

Publications by Sara van de Geer have appeared across a range of venues. These include:

  • arXiv (Cornell University)
  • The Annals of Statistics
  • Mathematical Statistics and Learning
  • Oberwolfach Reports
  • SIAM/ASA Journal on Uncertainty Quantification

Recent papers from their research portfolio are:

  • Convergence Rates for Penalized Least Squares Estimators in PDE Constrained Regression Problems, 2020, SIAM/ASA Journal on Uncertainty Quantification
  • De-Biased Sparse PCA: Inference for Eigenstructure of Large Covariance Matrices, 2021, IEEE Transactions on Information Theory
  • Prediction bounds for higher order total variation regularized least squares, 2021, The Annals of Statistics
  • On the robustness of minimum norm interpolators and regularized empirical risk minimizers, 2022, The Annals of Statistics
  • AdaBoost and robust one-bit compressed sensing, 2022, Mathematical Statistics and Learning

Sara van de Geer is recognized as a member of Academia Europaea since 2020 and was the Wald Memorial Lecturer in 2016.

Best Publications

  • Statistics for High-Dimensional Data: Methods, Theory and Applications

    Peter Bhlmann;Sara van de Geer

  • The group lasso for logistic regression

    Lukas Meier;Sara Van De Geer;Peter Bühlmann

  • On asymptotically optimal confidence regions and tests for high-dimensional models

    Sara van de Geer;Peter Bühlmann;Ya’acov Ritov;Ruben Dezeure

  • A global test for groups of genes: testing association with a clinical outcome

    Jelle J. Goeman;Sara A. Van De Geer;Floor De Kort;Hans C. Van Houwelingen

  • Empirical Processes in M-Estimation

    Sara A. van de Geer

  • High-dimensional generalized linear models and the lasso

    Sara A. van de Geer

  • On the conditions used to prove oracle results for the Lasso

    Sara A. van de Geer;Peter Bühlmann

  • High-dimensional additive modeling

    Lukas Meier;Sara van de Geer;Peter Bühlmann

  • Oracle Inequalities and Optimal Inference under Group Sparsity

    Karim Lounici;Massimiliano Pontil;Sara van de Geer;Alexandre B. Tsybakov

  • Locally adaptive regression splines

    Enno Mammen;Sara van de Geer

  • ℓ1-penalization for mixture regression models

    Nicolas Städler;Peter Bühlmann;Sara van de Geer

  • Regularization in Statistics

    Peter J. Bickel;Bo Li;Alexandre B. Tsybakov;Sara A. van de Geer

  • Testing against a high dimensional alternative

    Jelle J. Goeman;Sara A. Van De Geer;Hans C. Van Houwelingen

  • Ecole d'été de probabilités de Saint-Flour XLV

    Sara van de Geer

  • Taking Advantage of Sparsity in Multi-Task Learning

    Karim Lounici;Massimiliano Pontil;Alexandre B. Tsybakov;Sara A. van de Geer

  • Hellinger-Consistency of Certain Nonparametric Maximum Likelihood Estimators

    Sara van de Geer

  • Correlated variables in regression: Clustering and sparse estimation

    Peter Bühlmann;Philipp Rütimann;Sara van de Geer;Cun-Hui Zhang

  • Estimating a Regression Function

    Sara van de Geer

  • Estimation for High‐Dimensional Linear Mixed‐Effects Models Using ℓ1‐Penalization

    Jürg Schelldorfer;Peter Bühlmann;Sara Van De Geer

  • Confidence intervals for high-dimensional inverse covariance estimation

    Jana Janková;Sara van de Geer

  • Penalized quasi-likelihood estimation in partial linear models

    Enno Mammen;Sara van de Geer

Frequent Co-Authors

Alexandre B. Tsybakov
Alexandre B. Tsybakov École Nationale de la Statistique et de l'Administration Économique
Jon A. Wellner
Jon A. Wellner University of Washington
Enno Mammen
Enno Mammen Heidelberg University
Vladimir Koltchinskii
Vladimir Koltchinskii Georgia Institute of Technology
Massimiliano Pontil
Massimiliano Pontil Italian Institute of Technology
Arie Kapteyn
Arie Kapteyn University of Southern California
Bin Yu
Bin Yu University of California, Berkeley
Leen Stougie
Leen Stougie Centrum Wiskunde & Informatica

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