ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1507.00407
  4. Cited By
Fast Convergence of Regularized Learning in Games
v1v2v3v4v5 (latest)

Fast Convergence of Regularized Learning in Games

2 July 2015
Vasilis Syrgkanis
Alekh Agarwal
Haipeng Luo
Robert Schapire
ArXiv (abs)PDFHTML

Papers citing "Fast Convergence of Regularized Learning in Games"

28 / 128 papers shown
Title
Dynamic Regret of Convex and Smooth Functions
Dynamic Regret of Convex and Smooth Functions
Peng Zhao
Yu Zhang
Lijun Zhang
Zhi Zhou
104
105
0
07 Jul 2020
Dynamic Regret of Policy Optimization in Non-stationary Environments
Dynamic Regret of Policy Optimization in Non-stationary Environments
Yingjie Fei
Zhuoran Yang
Zhaoran Wang
Qiaomin Xie
100
56
0
30 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
139
11
0
16 Jun 2020
Minimax Estimation of Conditional Moment Models
Minimax Estimation of Conditional Moment Models
Nishanth Dikkala
Greg Lewis
Lester W. Mackey
Vasilis Syrgkanis
226
103
0
12 Jun 2020
Taking a hint: How to leverage loss predictors in contextual bandits?
Taking a hint: How to leverage loss predictors in contextual bandits?
Chen-Yu Wei
Haipeng Luo
Alekh Agarwal
178
27
0
04 Mar 2020
From Poincaré Recurrence to Convergence in Imperfect Information
  Games: Finding Equilibrium via Regularization
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization
Julien Perolat
Rémi Munos
Jean-Baptiste Lespiau
Shayegan Omidshafiei
Mark Rowland
...
David Balduzzi
Bart De Vylder
Georgios Piliouras
Marc Lanctot
K. Tuyls
84
85
0
19 Feb 2020
Last iterate convergence in no-regret learning: constrained min-max
  optimization for convex-concave landscapes
Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes
Qi Lei
Sai Ganesh Nagarajan
Ioannis Panageas
Tianlin Li
79
46
0
17 Feb 2020
Online and Bandit Algorithms for Nonstationary Stochastic Saddle-Point
  Optimization
Online and Bandit Algorithms for Nonstationary Stochastic Saddle-Point Optimization
Abhishek Roy
Yifang Chen
Krishnakumar Balasubramanian
P. Mohapatra
97
25
0
03 Dec 2019
No-Regret Learning in Unknown Games with Correlated Payoffs
No-Regret Learning in Unknown Games with Correlated Payoffs
Pier Giuseppe Sessa
Ilija Bogunovic
Maryam Kamgarpour
Andreas Krause
OffRL
105
40
0
18 Sep 2019
No-regret Learning in Cournot Games
No-regret Learning in Cournot Games
Yuanyuan Shi
Baosen Zhang
56
4
0
15 Jun 2019
ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring
  for Minimax Problems
ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems
Ernest K. Ryu
Kun Yuan
W. Yin
94
37
0
26 May 2019
Differentiable Game Mechanics
Differentiable Game Mechanics
Alistair Letcher
David Balduzzi
S. Racanière
James Martens
Jakob N. Foerster
K. Tuyls
T. Graepel
90
81
0
13 May 2019
Introduction to Multi-Armed Bandits
Introduction to Multi-Armed Bandits
Aleksandrs Slivkins
706
1,025
0
15 Apr 2019
Robust Multi-agent Counterfactual Prediction
Robust Multi-agent Counterfactual Prediction
A. Peysakhovich
Christian Kroer
Adam Lerer
45
11
0
03 Apr 2019
Stable-Predictive Optimistic Counterfactual Regret Minimization
Stable-Predictive Optimistic Counterfactual Regret Minimization
Gabriele Farina
Christian Kroer
Noam Brown
Tuomas Sandholm
98
34
0
13 Feb 2019
Learning to Collaborate in Markov Decision Processes
Learning to Collaborate in Markov Decision Processes
Goran Radanović
R. Devidze
David C. Parkes
Adish Singla
105
33
0
23 Jan 2019
Adversarial Bandits with Knapsacks
Adversarial Bandits with Knapsacks
Nicole Immorlica
Karthik Abinav Sankararaman
Robert Schapire
Aleksandrs Slivkins
213
116
0
28 Nov 2018
Bandit learning in concave $N$-person games
Bandit learning in concave NNN-person games
Mario Bravo
David S. Leslie
P. Mertikopoulos
69
123
0
03 Oct 2018
Solving Imperfect-Information Games via Discounted Regret Minimization
Solving Imperfect-Information Games via Discounted Regret Minimization
Noam Brown
Tuomas Sandholm
161
168
0
11 Sep 2018
Acceleration through Optimistic No-Regret Dynamics
Acceleration through Optimistic No-Regret Dynamics
Jun-Kun Wang
Jacob D. Abernethy
190
45
0
27 Jul 2018
Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max
  Optimization
Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization
C. Daskalakis
Ioannis Panageas
110
181
0
11 Jul 2018
Adversarial Generalized Method of Moments
Adversarial Generalized Method of Moments
Greg Lewis
Vasilis Syrgkanis
GAN
42
59
0
19 Mar 2018
More Adaptive Algorithms for Adversarial Bandits
More Adaptive Algorithms for Adversarial Bandits
Chen-Yu Wei
Haipeng Luo
183
185
0
10 Jan 2018
Training GANs with Optimism
Training GANs with Optimism
C. Daskalakis
Andrew Ilyas
Vasilis Syrgkanis
Haoyang Zeng
200
520
0
31 Oct 2017
Dynamic Pricing in Competitive Markets
Dynamic Pricing in Competitive Markets
Paresh Nakhe
24
2
0
14 Sep 2017
Cycles in adversarial regularized learning
Cycles in adversarial regularized learning
P. Mertikopoulos
Christos H. Papadimitriou
Georgios Piliouras
91
323
0
08 Sep 2017
Efficient Algorithms for Adversarial Contextual Learning
Efficient Algorithms for Adversarial Contextual Learning
Vasilis Syrgkanis
A. Krishnamurthy
Robert Schapire
179
80
0
08 Feb 2016
Semantics, Representations and Grammars for Deep Learning
Semantics, Representations and Grammars for Deep Learning
David Balduzzi
GNN
44
1
0
29 Sep 2015
Previous
123