Ya-Ping Hsieh | Learning & Adaptive Systems Group

Ya-Ping Hsieh

Postdoctoral Fellow
External Website
yaping.hsieh@inf.ethz.ch
CAB F 61.1

Publications

2024
Sinkhorn Flow as Mirror Flow: A Continuous-Time Framework for Generalizing the Sinkhorn Algorithm M. R. Karimi, Y. P. Hsieh, A. Krause In Proc. International Conference on Artificial Intelligence and Statistics (AISTATS), 2024 [bibtex] [abstract] [pdf]
2023
A Dynamical System View of Langevin-Based Non-Convex Sampling M. R. Karimi, Y. P. Hsieh, A. Krause In Proc. of Thirty Seventh Conference on Neural Information Processing Systems (NeurIPS), 2023 [bibtex] [abstract]
Stochastic Approximation Algorithms for Systems of Interacting Particles M. R. Karimi, Y. P. Hsieh, A. Krause In Proc. of Thirty Seventh Conference on Neural Information Processing Systems (NeurIPS), 2023 [bibtex] [abstract]
Riemannian stochastic optimization methods avoid strict saddle points Y. P. Hsieh, M. R. Karimi, A. Krause, P. Mertikopoulos In Proc. of Thirty Seventh Conference on Neural Information Processing Systems (NeurIPS), 2023 [bibtex] [abstract]
Aligned Diffusion Schrödinger Bridges V. R. Somnath, M. Pariset, Y. P. Hsieh, M. R. Martinez, A. Krause, C. Bunne In Conference on Uncertainty in Artificial Intelligence (UAI), 2023 Spotlight presentation [bibtex] [abstract] [pdf]
Unbalanced Diffusion Schrödinger Bridge M. Pariset, Y. P. Hsieh, C. Bunne, A. Krause, V. D. Bortoli In arXiv Preprint arXiv:2306.09099v1, 2023 [bibtex] [abstract] [pdf]
The Schrödinger Bridge between Gaussian Measures has a Closed Form C. Bunne, Y. P. Hsieh, M. Cuturi, A. Krause In Proc. International Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Oral presentation [bibtex] [abstract] [pdf]
2022
Continuous-time Analysis for Variational Inequalities: An Overview and Desiderata T. Chavdarova, Y. P. Hsieh, M. I. Jordan In arXiv preprint arXiv:2207.07105, 2022 [bibtex] [abstract] [pdf]
The Dynamics of Riemannian Robbins-Monro Algorithms M. R. Karimi, Y. P. Hsieh, P. Mertikopoulos, A. Krause In Proc. of Thirty Fifth Conference on Learning Theory (COLT), 2022 [bibtex] [abstract] [pdf]
Learning in games from a stochastic approximation viewpoint P. Mertikopoulos, Y. P. Hsieh, V. Cevher In arXiv preprint arXiv:2206.03922, 2022 [bibtex] [abstract] [pdf]
2021
The limits of min-max optimization algorithms: Convergence to spurious non-critical sets Y. P. Hsieh, P. Mertikopoulos, V. Cevher In Proc. of Thirty Eighth International Conference on Machine Learning (ICML), 2021 [bibtex] [abstract] [pdf]
2020
Robust Reinforcement Learning via Adversarial training with Langevin Dynamics K. Parameswaran, Y. T. Huang, Y. P. Hsieh, P. T. Y. Rolland, C. Shi, V. Cevher In Neural Information Processing Systems (NeurIPS), 2020 [bibtex] [abstract] [pdf]