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Optimistic mirror descent in saddle-point problems: Going the extra
  (gradient) mile

Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile

7 July 2018
P. Mertikopoulos
Bruno Lecouat
Houssam Zenati
Chuan-Sheng Foo
V. Chandrasekhar
Georgios Piliouras
ArXivPDFHTML

Papers citing "Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile"

50 / 60 papers shown
Title
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
Tianyi Lin
Chi Jin
Michael I. Jordan
52
7
0
28 Jan 2025
On the Interplay between Social Welfare and Tractability of Equilibria
On the Interplay between Social Welfare and Tractability of Equilibria
Ioannis Anagnostides
T. Sandholm
62
2
0
10 Jan 2025
Magnetic Preference Optimization: Achieving Last-iterate Convergence for Language Model Alignment
Magnetic Preference Optimization: Achieving Last-iterate Convergence for Language Model Alignment
Mingzhi Wang
Chengdong Ma
Qizhi Chen
Linjian Meng
Yang Han
Jiancong Xiao
Zhaowei Zhang
Jing Huo
Weijie Su
Yaodong Yang
32
5
0
22 Oct 2024
Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms
Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms
Yang Cai
Gabriele Farina
Julien Grand-Clément
Christian Kroer
Chung-Wei Lee
Haipeng Luo
Weiqiang Zheng
58
6
0
15 Jun 2024
A geometric decomposition of finite games: Convergence vs. recurrence
  under exponential weights
A geometric decomposition of finite games: Convergence vs. recurrence under exponential weights
Davide Legacci
P. Mertikopoulos
Bary S. R. Pradelski
37
6
0
12 May 2024
Dealing with unbounded gradients in stochastic saddle-point optimization
Dealing with unbounded gradients in stochastic saddle-point optimization
Gergely Neu
Nneka Okolo
37
3
0
21 Feb 2024
Nash Equilibrium and Learning Dynamics in Three-Player Matching $m$-Action Games
Nash Equilibrium and Learning Dynamics in Three-Player Matching mmm-Action Games
Yuma Fujimoto
Kaito Ariu
Kenshi Abe
29
1
0
16 Feb 2024
Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games
Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games
Yang Cai
Gabriele Farina
Julien Grand-Clément
Christian Kroer
Chung-Wei Lee
Haipeng Luo
Weiqiang Zheng
33
1
0
01 Nov 2023
Generating Less Certain Adversarial Examples Improves Robust Generalization
Generating Less Certain Adversarial Examples Improves Robust Generalization
Minxing Zhang
Michael Backes
Xiao Zhang
AAML
40
1
0
06 Oct 2023
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions
Multi-Player Zero-Sum Markov Games with Networked Separable Interactions
Chanwoo Park
Kaipeng Zhang
Asuman Ozdaglar
30
8
0
13 Jul 2023
First Order Methods with Markovian Noise: from Acceleration to
  Variational Inequalities
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities
Aleksandr Beznosikov
S. Samsonov
Marina Sheshukova
Alexander Gasnikov
A. Naumov
Eric Moulines
46
14
0
25 May 2023
Memory Asymmetry Creates Heteroclinic Orbits to Nash Equilibrium in
  Learning in Zero-Sum Games
Memory Asymmetry Creates Heteroclinic Orbits to Nash Equilibrium in Learning in Zero-Sum Games
Yuma Fujimoto
Kaito Ariu
Kenshi Abe
34
2
0
23 May 2023
Beyond first-order methods for non-convex non-concave min-max
  optimization
Beyond first-order methods for non-convex non-concave min-max optimization
Abhijeet Vyas
Brian Bullins
31
1
0
17 Apr 2023
Sublinear Convergence Rates of Extragradient-Type Methods: A Survey on
  Classical and Recent Developments
Sublinear Convergence Rates of Extragradient-Type Methods: A Survey on Classical and Recent Developments
Quoc Tran-Dinh
35
7
0
30 Mar 2023
Single-Call Stochastic Extragradient Methods for Structured Non-monotone
  Variational Inequalities: Improved Analysis under Weaker Conditions
Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions
S. Choudhury
Eduard A. Gorbunov
Nicolas Loizou
27
13
0
27 Feb 2023
Balanced Off-Policy Evaluation for Personalized Pricing
Balanced Off-Policy Evaluation for Personalized Pricing
Adam N. Elmachtoub
Vishal Gupta
Yunfan Zhao
OffRL
37
6
0
24 Feb 2023
Escaping limit cycles: Global convergence for constrained
  nonconvex-nonconcave minimax problems
Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems
Thomas Pethick
P. Latafat
Panagiotis Patrinos
Olivier Fercoq
V. Cevher
41
45
0
20 Feb 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient
  Communications for Distributed Variational Inequalities
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities
Aleksandr Beznosikov
Martin Takáč
Alexander Gasnikov
31
10
0
15 Feb 2023
Learning in Multi-Memory Games Triggers Complex Dynamics Diverging from
  Nash Equilibrium
Learning in Multi-Memory Games Triggers Complex Dynamics Diverging from Nash Equilibrium
Yuma Fujimoto
Kaito Ariu
Kenshi Abe
28
4
0
02 Feb 2023
Provable Reset-free Reinforcement Learning by No-Regret Reduction
Provable Reset-free Reinforcement Learning by No-Regret Reduction
Hoai-An Nguyen
Ching-An Cheng
OffRL
26
2
0
06 Jan 2023
Explicit Second-Order Min-Max Optimization Methods with Optimal
  Convergence Guarantee
Explicit Second-Order Min-Max Optimization Methods with Optimal Convergence Guarantee
Tianyi Lin
P. Mertikopoulos
Michael I. Jordan
31
11
0
23 Oct 2022
Last-Iterate Convergence with Full and Noisy Feedback in Two-Player
  Zero-Sum Games
Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games
Kenshi Abe
Kaito Ariu
Mitsuki Sakamoto
Kenta Toyoshima
Atsushi Iwasaki
34
11
0
21 Aug 2022
The Power of Regularization in Solving Extensive-Form Games
The Power of Regularization in Solving Extensive-Form Games
Ming Liu
Asuman Ozdaglar
Tiancheng Yu
Kaipeng Zhang
29
20
0
19 Jun 2022
On Scaled Methods for Saddle Point Problems
On Scaled Methods for Saddle Point Problems
Aleksandr Beznosikov
Aibek Alanov
D. Kovalev
Martin Takáč
Alexander Gasnikov
30
4
0
16 Jun 2022
Alternating Mirror Descent for Constrained Min-Max Games
Alternating Mirror Descent for Constrained Min-Max Games
Andre Wibisono
Molei Tao
Georgios Piliouras
37
14
0
08 Jun 2022
Federated Minimax Optimization: Improved Convergence Analyses and
  Algorithms
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms
Pranay Sharma
Rohan Panda
Gauri Joshi
P. Varshney
FedML
21
47
0
09 Mar 2022
Semi-Implicit Hybrid Gradient Methods with Application to Adversarial
  Robustness
Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness
Beomsu Kim
Junghoon Seo
AAML
22
0
0
21 Feb 2022
Simultaneous Transport Evolution for Minimax Equilibria on Measures
Carles Domingo-Enrich
Joan Bruna
23
3
0
14 Feb 2022
Optimal Algorithms for Decentralized Stochastic Variational Inequalities
Optimal Algorithms for Decentralized Stochastic Variational Inequalities
D. Kovalev
Aleksandr Beznosikov
Abdurakhmon Sadiev
Michael Persiianov
Peter Richtárik
Alexander Gasnikov
37
35
0
06 Feb 2022
Faster Single-loop Algorithms for Minimax Optimization without Strong
  Concavity
Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity
Junchi Yang
Antonio Orvieto
Aurelien Lucchi
Niao He
27
62
0
10 Dec 2021
Convergence of sequences: a survey
Convergence of sequences: a survey
Barbara Franci
Sergio Grammatico
36
19
0
22 Nov 2021
No-Regret Dynamics in the Fenchel Game: A Unified Framework for
  Algorithmic Convex Optimization
No-Regret Dynamics in the Fenchel Game: A Unified Framework for Algorithmic Convex Optimization
Jun-Kun Wang
Jacob D. Abernethy
Kfir Y. Levy
27
21
0
22 Nov 2021
Uncoupled Bandit Learning towards Rationalizability: Benchmarks,
  Barriers, and Algorithms
Uncoupled Bandit Learning towards Rationalizability: Benchmarks, Barriers, and Algorithms
Jibang Wu
Haifeng Xu
Fan Yao
30
1
0
10 Nov 2021
GDA-AM: On the effectiveness of solving minimax optimization via
  Anderson Acceleration
GDA-AM: On the effectiveness of solving minimax optimization via Anderson Acceleration
Huan He
Shifan Zhao
Yuanzhe Xi
Joyce C. Ho
Y. Saad
34
1
0
06 Oct 2021
Distributed stochastic optimization with large delays
Distributed stochastic optimization with large delays
Zhengyuan Zhou
P. Mertikopoulos
Nicholas Bambos
Peter Glynn
Yinyu Ye
28
9
0
06 Jul 2021
Decentralized Local Stochastic Extra-Gradient for Variational
  Inequalities
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities
Aleksandr Beznosikov
Pavel Dvurechensky
Anastasia Koloskova
V. Samokhin
Sebastian U. Stich
Alexander Gasnikov
32
43
0
15 Jun 2021
A Game-Theoretic Approach to Multi-Agent Trust Region Optimization
A Game-Theoretic Approach to Multi-Agent Trust Region Optimization
Ying Wen
Hui Chen
Yaodong Yang
Zheng Tian
Minne Li
Xu Chen
Jun Wang
38
11
0
12 Jun 2021
A Decentralized Adaptive Momentum Method for Solving a Class of Min-Max
  Optimization Problems
A Decentralized Adaptive Momentum Method for Solving a Class of Min-Max Optimization Problems
Babak Barazandeh
Tianjian Huang
George Michailidis
27
12
0
10 Jun 2021
Adaptive Learning in Continuous Games: Optimal Regret Bounds and
  Convergence to Nash Equilibrium
Adaptive Learning in Continuous Games: Optimal Regret Bounds and Convergence to Nash Equilibrium
Yu-Guan Hsieh
Kimon Antonakopoulos
P. Mertikopoulos
18
75
0
26 Apr 2021
Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max
  Optimization
Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization
Haochuan Li
Yi Tian
Jingzhao Zhang
Ali Jadbabaie
24
40
0
18 Apr 2021
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization
Siqi Zhang
Junchi Yang
Cristóbal Guzmán
Negar Kiyavash
Niao He
33
61
0
29 Mar 2021
Learning in Matrix Games can be Arbitrarily Complex
Learning in Matrix Games can be Arbitrarily Complex
Gabriel P. Andrade
Rafael Frongillo
Georgios Piliouras
15
31
0
05 Mar 2021
Local Stochastic Gradient Descent Ascent: Convergence Analysis and
  Communication Efficiency
Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency
Yuyang Deng
M. Mahdavi
30
59
0
25 Feb 2021
A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems
A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems
Jiawei Zhang
Peijun Xiao
Ruoyu Sun
Zhi-Quan Luo
33
97
0
29 Oct 2020
Adaptive extra-gradient methods for min-max optimization and games
Adaptive extra-gradient methods for min-max optimization and games
Kimon Antonakopoulos
E. V. Belmega
P. Mertikopoulos
64
46
0
22 Oct 2020
Adaptive and Universal Algorithms for Variational Inequalities with
  Optimal Convergence
Adaptive and Universal Algorithms for Variational Inequalities with Optimal Convergence
Alina Ene
Huy Le Nguyen
27
14
0
15 Oct 2020
A Hölderian backtracking method for min-max and min-min problems
A Hölderian backtracking method for min-max and min-min problems
Jérôme Bolte
Lilian E. Glaudin
Edouard Pauwels
M. Serrurier
29
9
0
17 Jul 2020
A Convergent and Dimension-Independent Min-Max Optimization Algorithm
A Convergent and Dimension-Independent Min-Max Optimization Algorithm
Vijay Keswani
Oren Mangoubi
Sushant Sachdeva
Nisheeth K. Vishnoi
15
1
0
22 Jun 2020
On the Almost Sure Convergence of Stochastic Gradient Descent in
  Non-Convex Problems
On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems
P. Mertikopoulos
Nadav Hallak
Ali Kavis
V. Cevher
30
85
0
19 Jun 2020
Linear Last-iterate Convergence in Constrained Saddle-point Optimization
Linear Last-iterate Convergence in Constrained Saddle-point Optimization
Chen-Yu Wei
Chung-Wei Lee
Mengxiao Zhang
Haipeng Luo
19
11
0
16 Jun 2020
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