Hsieh, Ya-Ping

21 publications

NeurIPS 2025 Flow Density Control: Generative Optimization Beyond Entropy-Regularized Fine-Tuning Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause

ICML 2025 Provable Maximum Entropy Manifold Exploration via Diffusion Models Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause

ICLRW 2025 Provable Maximum Entropy Manifold Exploration via Diffusion Models Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause

AISTATS 2024 Sinkhorn Flow as Mirror Flow: A Continuous-Time Framework for Generalizing the Sinkhorn Algorithm Mohammad Reza Karimi, Ya-Ping Hsieh, Andreas Krause

NeurIPS 2023 A Dynamical System View of Langevin-Based Non-Convex Sampling Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause

UAI 2023 Aligned Diffusion Schrödinger Bridges Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh, Maria Rodriguez Martinez, Andreas Krause, Charlotte Bunne

ICMLW 2023 Aligned Diffusion Schrödinger Bridges Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh, Maria Rodriguez Martinez, Andreas Krause, Charlotte Bunne

NeurIPS 2023 Riemannian Stochastic Optimization Methods Avoid Strict Saddle Points Ya-Ping Hsieh, Mohammad Reza Karimi Jaghargh, Andreas Krause, Panayotis Mertikopoulos

NeurIPS 2023 Stochastic Approximation Algorithms for Systems of Interacting Particles Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause

AISTATS 2023 The Schrödinger Bridge Between Gaussian Measures Has a Closed Form Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause

ICMLW 2023 Unbalanced Diffusion Schrödinger Bridge Matteo Pariset, Ya-Ping Hsieh, Charlotte Bunne, Andreas Krause, Valentin De Bortoli

COLT 2022 The Dynamics of Riemannian Robbins-Monro Algorithms Mohammad Reza Karimi, Ya-Ping Hsieh, Panayotis Mertikopoulos, Andreas Krause

ICML 2021 The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher

ICML 2020 Conditional Gradient Methods for Stochastically Constrained Convex Minimization Maria-Luiza Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh, Volkan Cevher

NeurIPS 2020 Robust Reinforcement Learning via Adversarial Training with Langevin Dynamics Parameswaran Kamalaruban, Yu-Ting Huang, Ya-Ping Hsieh, Paul Rolland, Cheng Shi, Volkan Cevher

ICML 2019 Finding Mixed Nash Equilibria of Generative Adversarial Networks Ya-Ping Hsieh, Chen Liu, Volkan Cevher

ALT 2018 Dimension-Free Information Concentration via Exp-Concavity Ya-ping Hsieh, Volkan Cevher

ICML 2018 Let’s Be Honest: An Optimal No-Regret Framework for Zero-Sum Games Ehsan Asadi Kangarshahi, Ya-Ping Hsieh, Mehmet Fatih Sahin, Volkan Cevher

NeurIPS 2018 Mirrored Langevin Dynamics Ya-Ping Hsieh, Ali Kavis, Paul Rolland, Volkan Cevher

NeurIPS 2016 An Efficient Streaming Algorithm for the Submodular Cover Problem Ashkan Norouzi-Fard, Abbas Bazzi, Ilija Bogunovic, Marwa El Halabi, Ya-Ping Hsieh, Volkan Cevher

NeurIPS 2015 Preconditioned Spectral Descent for Deep Learning David E Carlson, Edo Collins, Ya-Ping Hsieh, Lawrence Carin, Volkan Cevher