Ya-Ping Hsieh

According to our database, Ya-Ping Hsieh authored at least 39 papers between 2012 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Support Before Frequency in Discrete Diffusion.

Adrian Müller, Antoine Gonon, Zebang Shen, Ya-Ping Hsieh, Niao He

CoRR, May, 2026

Manifold Generalization Provably Proceeds Memorization in Diffusion Models.

Zebang Shen, Ya-Ping Hsieh, Niao He

CoRR, March, 2026

Verifier-Constrained Flow Expansion for Discovery Beyond the Data.

Riccardo De Santi, Kimon Protopapas, Ya-Ping Hsieh, Andreas Krause

CoRR, February, 2026

A Unified Density Operator View of Flow Control and Merging.

Riccardo De Santi, Malte Franke, Ya-Ping Hsieh, Andreas Krause

CoRR, February, 2026

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

CoRR, November, 2025

When Scores Learn Geometry: Rate Separations under the Manifold Hypothesis.

Xiang Li, Zebang Shen, Ya-Ping Hsieh, Niao He

CoRR, September, 2025

Provable Maximum Entropy Manifold Exploration via Diffusion Models.

Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

A unified stochastic approximation framework for learning in games.

Panayotis Mertikopoulos, Ya-Ping Hsieh, Volkan Cevher

Math. Program., January, 2024

Sinkhorn Flow as Mirror Flow: A Continuous-Time Framework for Generalizing the Sinkhorn Algorithm.

Mohammad Reza Karimi, Ya-Ping Hsieh, Andreas Krause

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Sinkhorn Flow: A Continuous-Time Framework for Understanding and Generalizing the Sinkhorn Algorithm.

Mohammad Reza Karimi, Ya-Ping Hsieh, Andreas Krause

CoRR, 2023

Unbalanced Diffusion Schrödinger Bridge.

Matteo Pariset, Ya-Ping Hsieh, Charlotte Bunne, Andreas Krause, Valentin De Bortoli

CoRR, 2023

Aligned Diffusion Schrödinger Bridges.

Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh, María Rodríguez Martínez, Andreas Krause, Charlotte Bunne

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Stochastic Approximation Algorithms for Systems of Interacting Particles.

Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Dynamical System View of Langevin-Based Non-Convex Sampling.

Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Riemannian stochastic optimization methods avoid strict saddle points.

Ya-Ping Hsieh, Mohammad Reza Karimi Jaghargh, Andreas Krause, Panayotis Mertikopoulos

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Schrödinger Bridge between Gaussian Measures has a Closed Form.

Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Continuous-time Analysis for Variational Inequalities: An Overview and Desiderata.

Tatjana Chavdarova, Ya-Ping Hsieh, Michael I. Jordan

CoRR, 2022

Learning in games from a stochastic approximation viewpoint.

Panayotis Mertikopoulos, Ya-Ping Hsieh, Volkan Cevher

CoRR, 2022

Recovering Stochastic Dynamics via Gaussian Schrödinger Bridges.

Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause

CoRR, 2022

The Dynamics of Riemannian Robbins-Monro Algorithms.

Mohammad Reza Karimi, Ya-Ping Hsieh, Panayotis Mertikopoulos, Andreas Krause

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets.

Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Robust Reinforcement Learning via Adversarial training with Langevin Dynamics.

Parameswaran Kamalaruban, Yu-Ting Huang, Ya-Ping Hsieh, Paul Rolland, Cheng Shi, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Conditional gradient methods for stochastically constrained convex minimization.

Maria-Luiza Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh, Volkan Cevher

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Finding Mixed Nash Equilibria of Generative Adversarial Networks.

Ya-Ping Hsieh, Chen Liu, Volkan Cevher

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization.

Ya-Ping Hsieh, Yu-Chun Kao, Rabeeh Karimi Mahabadi, Alp Yurtsever, Anastasios Kyrillidis, Volkan Cevher

IEEE Trans. Signal Process., 2018

Mirrored Langevin Dynamics.

Ya-Ping Hsieh, Volkan Cevher

CoRR, 2018

Mirrored Langevin Dynamics.

Ya-Ping Hsieh, Ali Kavis, Paul Rolland, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 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

Proceedings of the 35th International Conference on Machine Learning, 2018

Dimension-free Information Concentration via Exp-Concavity.

Ya-Ping Hsieh, Volkan Cevher

Proceedings of the Algorithmic Learning Theory, 2018

2016

Stochastic Spectral Descent for Discrete Graphical Models.

David E. Carlson, Ya-Ping Hsieh, Edo Collins, Lawrence Carin, Volkan Cevher

IEEE J. Sel. Top. Signal Process., 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

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Frank-Wolfe works for non-Lipschitz continuous gradient objectives: Scalable poisson phase retrieval.

Gergely Ódor, Yen-Huan Li, Alp Yurtsever, Ya-Ping Hsieh, Quoc Tran-Dinh, Marwa El Halabi, Volkan Cevher

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Estimation error of the constrained lasso.

Nissim Zerbib, Yen-Huan Li, Ya-Ping Hsieh, Volkan Cevher

Proceedings of the 54th Annual Allerton Conference on Communication, 2016

2015

Preconditioned Spectral Descent for Deep Learning.

David E. Carlson, Edo Collins, Ya-Ping Hsieh, Lawrence Carin, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Scalable convex methods for phase retrieval.

Alp Yurtsever, Ya-Ping Hsieh, Volkan Cevher

Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

2013

On the asynchronous information embedding for event-driven systems in molecular communications.

Ya-Ping Hsieh, Yen-Chi Lee, Po-Jen Shih, Ping-Cheng Yeh, Kwang-Cheng Chen

Nano Commun. Networks, 2013

Flexible transparent electrodes made of electrochemically exfoliated graphene sheets from low-cost graphite pieces.

Chuen-Ming Gee, Chien-Chih Tseng, Feng-Yu Wu, Hsin-Ping Chang, Lain-Jong Li, Ya-Ping Hsieh, Cheng-Te Lin, Jyh-Chen Chen

Displays, 2013

Mathematical Foundations for Information Theory in Diffusion-Based Molecular Communications.

Ya-Ping Hsieh, Ping-Cheng Yeh

CoRR, 2013

2012

An asynchronous communication scheme for molecular communication.

Ya-Ping Hsieh, Po-Jen Shih, Yen-Chi Lee, Ping-Cheng Yeh, Kwang-Cheng Chen

Proceedings of IEEE International Conference on Communications, 2012