Mahsa passed her doctoral exam, earning her doctorate in Mathematics from Ruhr-University Bochum. Great job, Dr. Taheri! 🎓
Paper on Targeted Deep Learning Accepted
Shih-Ting’s paper on targeted deep learning has been accepted at Stat. Good job, Shih-Ting! ⛰️
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.
Two new papers on deep learning
VIP Visitor
Professor Yuting Wei will visit us as a Visiting International Professor (VIP), a fellowship awarded by RUB to outstanding international researchers. Thank you, RUB! Congratulations, Yuting: well deserved! And congratulations to our PhD students, who helped make this possible! 🎉🎉
Electronic Journal of Statistics
Johannes has joined the editorial board of the Electronic Journal of Statistics. Find the journal’s website here.
Contributions to the GPSD 2023
We have four short lectures at the 16th German Probability and Statistics Days: The DeepCAR method: forecasting time-series data that have change points (presenter: Ayla), Lag selection and estimation of stable parameters for multiple autoregressive processes through convex programming (Somnath), Reducing computational and statistical complexity in machine learning through cardinality sparsity (Ali), and Extremes in high dimensions: statistical theories and scalable algorithms (M. Oesting, Stuttgart). Johannes co-organizes the sessions on Computational and high-dimensional statistics (with D. Rudolf, Passau). Looking forward to the conference!
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.
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.
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.
Johannes Lederer 