Johannes Lederer

Statistics, Machine Learning & Data Science

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Category Archives: Published Paper

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Posted by

LedererLab

Posted on

June 5, 2020

Posted under

Published Paper

High-dimensional inference

Our paper “Inference for high-dimensional instrumental variables regression” has now been published. Congratulations again to David and Jing!

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Posted by

LedererLab

Posted on

August 23, 2019

Posted under

Published Paper

Tuning Parameters in Logistic Regression

Our paper “Tuning parameter calibration for
l1-regularized logistic regression” has now been published in the Journal of Statistical Planning and Inference.

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Posted by

LedererLab

Posted on

June 15, 2019

Posted under

Published Paper

Prediction Guarantees for the TREX

Our paper “Prediction error bounds for linear regression with the TREX” has now been published in Test.

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Posted by

LedererLab

Posted on

March 6, 2019

Posted under

Published Paper

Oracle inequalities for high-dimensional prediction

Our paper on oracle inequalities is now published in Bernoulli 2019, Vol. 25, No. 2, 1225-1255. The weblink is here.

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Posted by

LedererLab

Posted on

June 1, 2018

Posted under

Published Paper

Maximum regularized likelihood estimators

Our paper “Maximum regularized likelihood estimators: A general prediction theory and applications” has now been published here.

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Posted by

LedererLab

Posted on

April 19, 2018

Posted under

Published Paper

Non-convex Optimization

Our paper “Non-Convex Global Minimization and False Discovery Rate Control for the TREX” has now been published here. The arXiv version can still be found here.

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