Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded
Geometric Penalties

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Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties

25 May 2023

David Martínez-Rubio

Christophe Roux

Christopher Criscitiello

Sebastian Pokutta

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Papers citing "Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties"

8 / 8 papers shown

Title
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 301 30,152 0 01 Mar 2022
$Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the $O(ε^{-7/4})$ Complexity$ Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the $O(ε^{-7/4})$ Complexity Huan Li Zhouchen Lin 98 24 0 27 Jan 2022
Escaping from saddle points on Riemannian manifolds Yue Sun Nicolas Flammarion Maryam Fazel 52 72 0 18 Jun 2019
Efficiently escaping saddle points on manifolds Christopher Criscitiello Nicolas Boumal 71 63 0 10 Jun 2019
A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach Aryan Mokhtari Asuman Ozdaglar S. Pattathil 106 328 0 24 Jan 2019
Learning Models with Uniform Performance via Distributionally Robust Optimization John C. Duchi Hongseok Namkoong OOD 95 424 0 20 Oct 2018
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds Hongyi Zhang Sashank J. Reddi S. Sra 112 241 0 23 May 2016
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,145 0 20 Dec 2014

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