16 citations · 73 across the 18 of their papers we have counts for
5 papers · 1 filter
A Dynamical System View of Langevin-Based Non-Convex Sampling
Mohammad Reza Karimi, Ya-Ping Hsieh, Andreas Krause
Non-convex sampling is a key challenge in machine learning, central to non-convex optimization in deep learning as well as to approximate probabilistic inference. Despite its signi…
Continuous-time Analysis for Variational Inequalities: An Overview and Desiderata
Tatjana Chavdarova, Ya-Ping Hsieh, Michael I. Jordan
Algorithms that solve zero-sum games, multi-objective agent objectives, or, more generally, variational inequality (VI) problems are notoriously unstable on general problems. Owing…
Riemannian stochastic approximation algorithms
Mohammad Reza Karimi, Ya-Ping Hsieh, Panayotis Mertikopoulos +1
We examine a wide class of stochastic approximation algorithms for solving (stochastic) nonlinear problems on Riemannian manifolds. Such algorithms arise naturally in the study of…
A unified stochastic approximation framework for learning in games
Panayotis Mertikopoulos, Ya-Ping Hsieh, Volkan Cevher
We develop a flexible stochastic approximation framework for analyzing the long-run behavior of learning in games (both continuous and finite). The proposed analysis template incor…
The Schrödinger Bridge between Gaussian Measures has a Closed Form
Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi +1
The static optimal transport problem between Gaussians seeks to recover an optimal map, or more generally a coupling, to morph a Gaussian into another. It has been…