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.
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! 🥇🥇
DeepMom paper now online
The published version of our paper “DeepMoM: Robust Deep Learning With Median-of-Means” is now accessible online
here.
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! 🤩
Canadian Journal of Statistics
Johannes has joined the editorial board of the Canadian Journal of Statistics. Find the journal’s website here.
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! 🕺🕺
Johannes Lederer 