Dominik Stöger

Dominik Stöger Email: stoger (at) usc (dot) edu Google Scholar

Short Bio:

• since 2019: postdoc at USC (Mentor: Mahdi Soltanolkotabi)

• 2016-2019: Ph.D. in Mathematics at Technical University of Munich (Advisor: Felix Krahmer)

• 2011-2015: B.Sc. and M.Sc. in Mathematics at Technical University of Munich

Research interests:

• Mathematics of data science

• Compressive sensing and low-rank matrix recovery

• High-dimensional probability and statistics

• Non-convex optimization in signal processing and machine learning

• Inductive bias of gradient descent

News:

• 12/2020: A new paper is on arXiv: “Iteratively Reweighted Least Squares for l1-minimization with Global Linear Convergence Rate” (joint with C. Kümmerle and C. Mayrink Verdun)

• 06/2020: my paper On the convex geometry of blind deconvolution and matrix completion, joint with Felix Krahmer, has been accepted for publication in Communications on Pure and Applied Mathematics

• 03/2020: awarded with the Dr.-Klaus-Körper Prize of GAMM for my dissertation

• 02/2020: seminar talk at UC San Diego