4 citations · 7 across the 2 of their papers we have counts for
9 papers
Unbalanced Diffusion Schrödinger Bridge
Matteo Pariset, Ya-Ping Hsieh, Charlotte Bunne +2
Schrödinger bridges (SBs) provide an elegant framework for modeling the temporal evolution of populations in physical, chemical, or biological systems. Such natural processes are c…
Conditional gradient methods for stochastically constrained convex minimization
Maria-Luiza Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh +1
We propose two novel conditional gradient-based methods for solving structured stochastic convex optimization problems with a large number of linear constraints. Instances of this…
The limits of min-max optimization algorithms: convergence to spurious non-critical sets
Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher
Compared to ordinary function minimization problems, min-max optimization algorithms encounter far greater challenges because of the existence of periodic cycles and similar phenom…
Robust Reinforcement Learning via Adversarial training with Langevin Dynamics
Parameswaran Kamalaruban, Yu-Ting Huang, Ya-Ping Hsieh +3
We introduce a sampling perspective to tackle the challenging task of training robust Reinforcement Learning (RL) agents. Leveraging the powerful Stochastic Gradient Langevin Dynam…
Finding Mixed Nash Equilibria of Generative Adversarial Networks
Ya-Ping Hsieh, Chen Liu, Volkan Cevher
We reconsider the training objective of Generative Adversarial Networks (GANs) from the mixed Nash Equilibria (NE) perspective. Inspired by the classical prox methods, we develop a…
Dimension-free Information Concentration via Exp-Concavity
Ya-Ping Hsieh, Volkan Cevher
Information concentration of probability measures have important implications in learning theory. Recently, it is discovered that the information content of a log-concave distribut…