I am an independent research group leader (equivalent to assistant professor) at the Weierstrass Institute for Applied Analysis and Stochastics, Berlin. Prior to coming to Berlin, I worked as a postdoctoral researcher in machine learning at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. My Ph.D. study was in optimization, with William Hager at the University of Florida. See here for a short bio.
I also write a non-research blog here. Though the frequency of updates depends on how busy I am at the moment.
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News and updates
- May 2023. Accepted paper at ICML 2023 (link to preprint): Heiner Kremer, Yassine Nemmour, Bernhard Sch ̈olkopf, and Jia-Jie Zhu. Estimation Beyond Data Reweighting: Kernel Method of Moments.
- May 2023. A couple of new preprints available:
- Apr 2023. Gave a plenary talk at the Leibniz Institute for Agricultural Engineering and Bioeconomy Potsdam, during the workshop “Mathematical Modeling and Simulation” (MMS) Days.
- Served as area chair for AISTATS 2023.
- Sep 2022. Here are the slides for a recent talk I gave at the OT workshop at TU Eindhoven.
- Aug 2022. Here (in both German and English) is a recent journal interview about my career path.
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Jul 2022. A few new publications at ICML and IEEE-CDC continuing previous works on kernel methods for robust optimization and control.
ICML paper on conditional moment problems for ML and causal inference
IEEE CDC paper on distributionally robust chance-constraint nonlinear optimization (preprint)
IEEE CDC paper on learning uncertain-aware dyanmics with large-scale kernel machines (preprint) - Jul 2022. I’m teaching a minicourse for the TU Berlin-Oxford IRTG Stochastic Analysis Ph.D. program. See exercise files and lecture notes.