Yassine Nemmour

Maximum Mean Discrepancy Distributionally Robust Nonlinear Chance-Constrained Optimization with Finite-Sample Guarantee

B. Schölkopf, Yassine Nemmour, Heiner Kremer, 2022, 2022 IEEE 61st Conference on Decision and Control (CDC).

Reliable Real Time Ball Tracking for Robot Table Tennis

Jan Peters, B. Schölkopf, S. Gómez-González, 2019, Robotics.

Learning Random Feature Dynamics for Uncertainty Quantification

B. Schölkopf, Jia-Jie Zhu, Diego Agudelo-España, 2022 .

Approximate Distributionally Robust Nonlinear Optimization with Application to Model Predictive Control: A Functional Approach

Bernhard Schölkopf, Yassine Nemmour, Jia-Jie Zhu, 2021, L4DC.

From Majorization to Interpolation: Distributionally Robust Learning using Kernel Smoothing pdf

Bernhard Schölkopf, Yassine Nemmour, Jia-Jie Zhu, 2021, ArXiv.

Distributional Robustness Regularized Scenario Optimization with Application to Model Predictive Control pdf

Bernhard Schölkopf, Yassine Nemmour, Jia-Jie Zhu, 2021, ArXiv.

Adversarially Robust Kernel Smoothing

Bernhard Scholkopf, Yassine Nemmour, Jia-Jie Zhu, 2021, AISTATS.

Estimation Beyond Data Reweighting: Kernel Method of Moments

B. Schölkopf, Yassine Nemmour, Heiner Kremer, 2023, ICML.

Shallow Representation is Deep: Learning Uncertainty-aware and Worst-case Random Feature Dynamics pdf

Bernhard Schölkopf, Diego Agudelo-España, Yassine Nemmour, 2021, ArXiv.