Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
1507.00407
Cited By
v1
v2
v3
v4
v5 (latest)
Fast Convergence of Regularized Learning in Games
2 July 2015
Vasilis Syrgkanis
Alekh Agarwal
Haipeng Luo
Robert Schapire
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Fast Convergence of Regularized Learning in Games"
28 / 128 papers shown
Title
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
Yingjie Fei
Zhuoran Yang
Zhaoran Wang
Qiaomin Xie
100
56
0
30 Jun 2020
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
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?
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
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
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
Abhishek Roy
Yifang Chen
Krishnakumar Balasubramanian
P. Mohapatra
97
25
0
03 Dec 2019
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
Yuanyuan Shi
Baosen Zhang
56
4
0
15 Jun 2019
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
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
Aleksandrs Slivkins
706
1,025
0
15 Apr 2019
Robust Multi-agent Counterfactual Prediction
A. Peysakhovich
Christian Kroer
Adam Lerer
45
11
0
03 Apr 2019
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
Goran Radanović
R. Devidze
David C. Parkes
Adish Singla
105
33
0
23 Jan 2019
Adversarial Bandits with Knapsacks
Nicole Immorlica
Karthik Abinav Sankararaman
Robert Schapire
Aleksandrs Slivkins
213
116
0
28 Nov 2018
Bandit learning in concave
N
N
N
-person games
Mario Bravo
David S. Leslie
P. Mertikopoulos
69
123
0
03 Oct 2018
Solving Imperfect-Information Games via Discounted Regret Minimization
Noam Brown
Tuomas Sandholm
161
168
0
11 Sep 2018
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
C. Daskalakis
Ioannis Panageas
110
181
0
11 Jul 2018
Adversarial Generalized Method of Moments
Greg Lewis
Vasilis Syrgkanis
GAN
42
59
0
19 Mar 2018
More Adaptive Algorithms for Adversarial Bandits
Chen-Yu Wei
Haipeng Luo
183
185
0
10 Jan 2018
Training GANs with Optimism
C. Daskalakis
Andrew Ilyas
Vasilis Syrgkanis
Haoyang Zeng
200
520
0
31 Oct 2017
Dynamic Pricing in Competitive Markets
Paresh Nakhe
24
2
0
14 Sep 2017
Cycles in adversarial regularized learning
P. Mertikopoulos
Christos H. Papadimitriou
Georgios Piliouras
91
323
0
08 Sep 2017
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
David Balduzzi
GNN
44
1
0
29 Sep 2015
Previous
1
2
3