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Empirical Inference Members Publications

Members

Empirical Inference
Jia-Jie Zhu
Empirical Inference
Wittawat Jitkrittum
Empirical Inference
Yassine Nemmour
  • Doctoral Researcher
Empirical Inference
Diego Alejandro Agudelo España
  • Doctoral Researcher

Publications

Empirical Inference Conference Paper Adversarially Robust Kernel Smoothing Zhu, J., Kouridi, C., Nemmour, Y., Schölkopf, B. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics, 151:4972-4994, Proceedings of Machine Learning Research, (Editors: Camps-Valls, Gustau and Ruiz, Francisco J. R. and Valera, Isabel), PMLR, 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022) , March 2022 (Published) arXiv URL BibTeX
Empirical Inference Conference Paper Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers Schmidt, R. M., Schneider, F., Hennig, P. Proceedings of 38th International Conference on Machine Learning (ICML), 139:9367-9376, Proceedings of Machine Learning Research, (Editors: Meila, Marina and Zhang, Tong), PMLR, July 2021 (Published) URL BibTeX
Empirical Inference Conference Paper Approximate Distributionally Robust Nonlinear Optimization with Application to Model Predictive Control: A Functional Approach Nemmour, Y., Schölkopf, B., Zhu, J. Proceedings of the 3rd Conference on Learning for Dynamics and Control (L4DC), 144:1255-1269, Proceedings of Machine Learning Research, (Editors: Jadbabaie, Ali and Lygeros, John and Pappas, George J. and Parrilo, Pablo A. and Recht, Benjamin and Tomlin, Claire J. and Zeilinger, Melanie N.), PMLR, June 2021 (Published) URL BibTeX
Empirical Inference Conference Paper Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation Zhu, J., Jitkrittum, W., Diehl, M., Schölkopf, B. Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 130:280-288, Proceedings of Machine Learning Research, (Editors: Arindam Banerjee and Kenji Fukumizu), PMLR, April 2021 (Published) arXiv URL BibTeX
Empirical Inference Miscellaneous Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative-Entropy Trust Regions Abdulsamad, H., Dorau, T., Belousov, B., Zhu, J., Peters, J. 2021 (Published) arXiv BibTeX
Empirical Inference Probabilistic Learning Group Conference Paper Relative gradient optimization of the Jacobian term in unsupervised deep learning Gresele, L., Fissore, G., Javaloy, A., Schölkopf, B., Hyvarinen, A. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 16567-16578, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX
Empirical Inference Conference Paper Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem Zhu, J., Jitkrittum, W., Diehl, M., Schölkopf, B. In 59th IEEE Conference on Decision and Control (CDC), 3457-3463, IEEE, December 2020 (Published) arXiv DOI BibTeX
Empirical Inference Conference Paper A New Distribution-Free Concept for Representing, Comparing, and Propagating Uncertainty in Dynamical Systems with Kernel Probabilistic Programming Zhu, J., Muandet, K., Diehl, M., Schölkopf, B. 21st IFAC World Congress, 53(2):7240-7247, July 2020 (Published) arXiv DOI BibTeX
Empirical Inference Conference Paper A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control Zhu, J., Diehl, M., Schölkopf, B. 2nd Annual Conference on Learning for Dynamics and Control (L4DC), 120:915-923, Proceedings of Machine Learning Research, (Editors: Alexandre M. Bayen and Ali Jadbabaie and George Pappas and Pablo A. Parrilo and Benjamin Recht and Claire Tomlin and Melanie Zeilinger), PMLR, June 2020 (Published) arXiv URL BibTeX