Zhu, Jia-Jie

11 publications

ICLRW 2025 Inclusive KL Minimization: A Wasserstein-Fisher-Rao Gradient Flow Perspective Jia-Jie Zhu

AISTATS 2024 Analysis of Kernel Mirror Prox for Measure Optimization Pavel Dvurechensky, Jia-Jie Zhu

NeurIPS 2024 Interaction-Force Transport Gradient Flows Egor Gladin, Pavel Dvurechensky, Alexander Mielke, Jia-Jie Zhu

ICML 2023 Estimation Beyond Data Reweighting: Kernel Method of Moments Heiner Kremer, Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu

ICMLW 2023 Kernel Mirror Prox and RKHS Gradient Flow for Mixed Functional Nash Equilibrium Pavel Dvurechensky, Jia-Jie Zhu

ICMLW 2023 Nonlinear Wasserstein Distributionally Robust Optimal Control Zhengang Zhong, Jia-Jie Zhu

AISTATS 2022 Adversarially Robust Kernel Smoothing Jia-Jie Zhu, Christina Kouridi, Yassine Nemmour, Bernhard Schölkopf

ICML 2022 Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions Heiner Kremer, Jia-Jie Zhu, Krikamol Muandet, Bernhard Schölkopf

AISTATS 2021 Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf

L4DC 2021 Approximate Distributionally Robust Nonlinear Optimization with Application to Model Predictive Control: A Functional Approach Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu

L4DC 2020 A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control Jia-Jie Zhu, Bernhard Schoelkopf, Moritz Diehl