Johannes Lederer

Statistical Learning, Artificial Intelligence & Data Science

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Author Archives: LedererLab

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LedererLab

Posted on

December 20, 2022

Posted under

Accepted Paper, New Paper

New Paper in AStA Adv. Stat. Anal.

We have a new paper with the title “Statistical guarantees for sparse deep learning” in AStA Adv. Stat. Anal.

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Posted by

LedererLab

Posted on

September 4, 2022

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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

August 23, 2022

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Accepted Paper

Paper Accepted at IEEE TIT

Our paper “Balancing Statistical and Computational Precision and Applications to Penalized Linear Regression with Group Sparsity” has been accepted at the IEEE Transactions on Information Theory. Well deserved, Néhémy and Mahsa! 🥇🥇

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LedererLab

Posted on

July 19, 2022

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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

July 12, 2022

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Team

Two new researchers on the team

We have two new researchers on our team: Somnath Chakraborty joins us as a post-doctoral researcher, and Ayşe Çobankaya will join us as a PhD student. Welcome! 🤩

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Posted by

LedererLab

Posted on

June 27, 2022

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Team

Canadian Journal of Statistics

Johannes has joined the editorial board of the Canadian Journal of Statistics. Find the journal’s website here.

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Posted by

LedererLab

Posted on

June 14, 2022

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Accepted Paper

Paper Accepted at JCGS

Our paper “DeepMoM: Robust Deep Learning With Median-of-Means” has been accepted at the Journal of Computational and Graphical Statistics. Awesome job, Shih-Ting! 🕺🕺

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LedererLab

Posted on

June 4, 2022

Posted under

Team

Shih-Ting passed final exams

Shih-Ting Huang passed his doctoral exam, earning his doctorate from Ruhr-University Bochum. Congratulations! 🎓

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Posted by

LedererLab

Posted on

May 17, 2022

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Accepted Paper

Paper Accepted at ICML

Our paper “Copula-Based Normalizing Flows” has been accepted at ICML. Cheers, Mike and Asja! 🥂

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Posted by

LedererLab

Posted on

May 11, 2022

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New Paper

Approximate Stationary Points of Simple Neural Networks

Our new paper “Statistical Guarantees for Approximate Stationary Points of Simple Neural Networks” is now online. Well done, Mahsa and Fang! 🎉🎉

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