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A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I
  Learned to Stop Worrying about Mixed-Nash and Love Neural Nets
v1v2v3 (latest)

A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets

14 February 2020
Gauthier Gidel
David Balduzzi
Wojciech M. Czarnecki
M. Garnelo
Yoram Bachrach
ArXiv (abs)PDFHTML

Papers citing "A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets"

4 / 4 papers shown
Exploiting hidden structures in non-convex games for convergence to Nash
  equilibrium
Exploiting hidden structures in non-convex games for convergence to Nash equilibrium
Iosif Sakos
Emmanouil-Vasileios Vlatakis-Gkaragkounis
P. Mertikopoulos
Georgios Piliouras
202
6
0
27 Dec 2023
Achieve Optimal Adversarial Accuracy for Adversarial Deep Learning using
  Stackelberg Game
Achieve Optimal Adversarial Accuracy for Adversarial Deep Learning using Stackelberg Game
Xiao-Shan Gao
Shuang Liu
Lijia Yu
AAML
315
1
0
17 Jul 2022
Complex Momentum for Optimization in Games
Complex Momentum for Optimization in GamesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Jonathan Lorraine
David Acuna
Paul Vicol
David Duvenaud
240
11
0
16 Feb 2021
Adversarial Example Games
Adversarial Example Games
A. Bose
Gauthier Gidel
Hugo Berrard
Andre Cianflone
Pascal Vincent
Damien Scieur
William L. Hamilton
AAMLGAN
479
57
0
01 Jul 2020
1
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