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06/15/2023
Unbalanced Diffusion Schrödinger Bridge
Schrödinger bridges (SBs) provide an elegant framework for modeling the ...
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02/22/2023
Aligned Diffusion Schrödinger Bridges
Diffusion Schrödinger bridges (DSB) have recently emerged as a powerful ...
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10/25/2022
A Dynamical System View of Langevin-Based Non-Convex Sampling
Non-convex sampling is a key challenge in machine learning, central to n...
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07/14/2022
Continuous-time Analysis for Variational Inequalities: An Overview and Desiderata
Algorithms that solve zero-sum games, multi-objective agent objectives, ...
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06/14/2022
The Dynamics of Riemannian Robbins-Monro Algorithms
Many important learning algorithms, such as stochastic gradient methods,...
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06/08/2022
Learning in games from a stochastic approximation viewpoint
We develop a unified stochastic approximation framework for analyzing th...
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02/11/2022
Recovering Stochastic Dynamics via Gaussian Schrödinger Bridges
We propose a new framework to reconstruct a stochastic process {ℙ_t: t ∈...
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07/07/2020
Conditional gradient methods for stochastically constrained convex minimization
We propose two novel conditional gradient-based methods for solving stru...
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06/16/2020
The limits of min-max optimization algorithms: convergence to spurious non-critical sets
Compared to minimization problems, the min-max landscape in machine lear...
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02/14/2020
Robust Reinforcement Learning via Adversarial training with Langevin Dynamics
We introduce a sampling perspective to tackle the challenging task of tr...
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10/23/2018
Finding Mixed Nash Equilibria of Generative Adversarial Networks
We reconsider the training objective of Generative Adversarial Networks ...
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02/27/2018
Mirrored Langevin Dynamics
We generalize the Langevin Dynamics through the mirror descent framework...
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02/26/2018
Dimension-free Information Concentration via Exp-Concavity
Information concentration of probability measures have important implica...
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02/12/2018
