Johannes Lederer

Statistical Learning, Artificial Intelligence & Data Science

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Category Archives: Published Paper

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Posted by

LedererLab

Posted on

February 25, 2023

Posted under

Published Paper

DeepMom paper published

Shih-Ting’s paper “DeepMoM: Robust Deep Learning With Median-of-Means” is now published in volume 32 of the Journal of Computational and Graphical Statistics. Find the paper here.

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Posted by

LedererLab

Posted on

January 2, 2023

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Published Paper

Lasso paper published

The published version of our paper “Balancing Statistical and Computational Precision: A General Theory and Applications to Sparse Regression” can now be found here.

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Posted by

LedererLab

Posted on

September 4, 2022

Posted under

Published Paper

Lasso paper now online

The final version of our paper “Balancing Statistical and Computational Precision: A General Theory and Applications to Sparse Regression” is now accessible online here.

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Posted by

LedererLab

Posted on

July 19, 2022

Posted under

Published Paper

DeepMom paper now online

The published version of our paper “DeepMoM: Robust Deep Learning With Median-of-Means” is now accessible online
here.

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Posted by

LedererLab

Posted on

April 12, 2022

Posted under

Published Paper

Graphical Models With the TREX

Our paper “Topology Adaptive Graph Estimation in High Dimensions” is now accepted and published in Mathematics here. Cheers, Christian! 🍺

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Posted by

LedererLab

Posted on

December 17, 2021

Posted under

Published Paper

Latest EJS Paper Published

Our paper “Tuning parameter calibration for personalized prediction in medicine” at EJS is now published here.

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Posted by

LedererLab

Posted on

December 1, 2021

Posted under

Published Paper

Latest JMLR Paper Online

Our paper “Estimating the lasso’s effective noise” at JMLR is now online here.

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Posted by

LedererLab

Posted on

May 17, 2021

Posted under

Published Paper

Regularized neural networks

The published version of “Statistical guarantees for regularized neural networks” can now be found
here.

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Posted by

LedererLab

Posted on

March 18, 2021

Posted under

Published Paper

Two recent biostats papers now online

The published versions of our papers “Tuning-free ridge estimators for high-dimensional generalized linear models” and “Integrating additional knowledge into the estimation of graphical models” are now accessible online
here and here, respectively.

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Posted by

LedererLab

Posted on

February 17, 2021

Posted under

Published Paper

FDR control rev.

Our paper “Aggregating Knockoffs for False Discovery Rate Control with an Application to Gut Microbiome Data” has now been published. Congratulations again to Fang!

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