Jia-Jie Zhu
Cited by
Cited by
Generative adversarial active learning
JJ Zhu, J Bento
arXiv preprint arXiv:1702.07956, 2017
Deep reinforcement learning for event-triggered control
D Baumann, JJ Zhu, G Martius, S Trimpe
2018 IEEE Conference on Decision and Control (CDC), 943-950, 2018
Kernel distributionally robust optimization: Generalized duality theorem and stochastic approximation
JJ Zhu, W Jitkrittum, M Diehl, B Schölkopf
International Conference on Artificial Intelligence and Statistics, 280-288, 2021
Control What You Can: Intrinsically Motivated Task-Planning Agent
S Blaes, MV Pogančić, JJ Zhu, G Martius
Advances in Neural Information Processing Systems, 2019, 2019
Robust Humanoid Locomotion Using Trajectory Optimization and Sample-Efficient Learning*
MH Yeganegi, M Khadiv, SAA Moosavian, JJ Zhu, A Del Prete, L Righetti
2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids …, 2019
Projection algorithms for nonconvex minimization with application to sparse principal component analysis
WW Hager, DT Phan, JJ Zhu
Journal of Global Optimization 65 (4), 657-676, 2016
A metric for sets of trajectories that is practical and mathematically consistent
J Bento, JJ Zhu
arXiv preprint arXiv:1601.03094, 2016
Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem
JJ Zhu, W Jitkrittum, M Diehl, B Schölkopf
2020 59th IEEE Conference on Decision and Control (CDC), 3457-3463, 2020
Fast Non-Parametric Learning to Accelerate Mixed-Integer Programming for Hybrid Model Predictive Control
JJ Zhu, G Martius
IFAC-PapersOnLine 53 (2), 5239-5245, 2020
Functional generalized empirical likelihood estimation for conditional moment restrictions
H Kremer, JJ Zhu, K Muandet, B Schölkopf
International Conference on Machine Learning, 11665-11682, 2022
A new distribution-free concept for representing, comparing, and propagating uncertainty in dynamical systems with kernel probabilistic programming
JJ Zhu, K Muandet, M Diehl, B Schölkopf
IFAC-PapersOnLine 53 (2), 7240-7247, 2020
A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control
JJ Zhu, M Diehl, B Schölkopf
Proceedings of the 2nd Conference on Learning for Dynamics and Control …, 2020
Maximum mean discrepancy distributionally robust nonlinear chance-constrained optimization with finite-sample guarantee
Y Nemmour, H Kremer, B Schölkopf, JJ Zhu
2022 IEEE 61st Conference on Decision and Control (CDC), 5660-5667, 2022
Adversarially Robust Kernel Smoothing
JJ Zhu, C Kouridi, Y Nemmour, B Schölkopf
arXiv preprint arXiv:2102.08474, 2021
A decentralized multi-block ADMM for demand-side primary frequency control using local frequency measurements
J Brooks, W Hager, J Zhu
arXiv preprint arXiv:1509.08206, 2015
Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative Entropy Trust-Regions
H Abdulsamad, T Dorau, B Belousov, JJ Zhu, J Peters
arXiv preprint arXiv:2103.15388, 2021
Distributional Robustness Regularized Scenario Optimization with Application to Model Predictive Control
Y Nemmour, B Schölkopf, JJ Zhu
arXiv preprint arXiv:2110.13588, 2021
Nonlinear Wasserstein Distributionally Robust Optimal Control
Z Zhong, JJ Zhu
arXiv preprint arXiv:2304.07415, 2023
A Mini-Course on Optimization and Dynamics: from Euclidean Gradient Descent to Wasserstein Gradient Flow
JJ Zhu
Estimation Beyond Data Reweighting: Kernel Method of Moments
H Kremer, Y Nemmour, B Schölkopf, JJ Zhu
arXiv preprint arXiv:2305.10898, 2023
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