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Owing to their connection with generative adversarial networks (GANs), saddle-point problems have recently attracted considerable interest in machine learning and beyond.
The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming
Bregman, Lev M. 1967 · 1967
Earlier work this paper cites.
Convex Analysis
Rockafellar, Ralph Tyrrell. 1970 · 1970
Earlier work this paper cites.
The extragradient method for finding saddle points and other problems
Korpelevich, G. M. 1976 · 1976
Earlier work this paper cites.
Martingale Limit Theory and Its Application
Hall, P., C. C. Heyde. 1980 · 1980
Earlier work this paper cites.
Problem Complexity and Method Efficiency in Optimization
Nemirovski, Arkadi Semen, David Berkovich Yudin. 1983 · 1983
Earlier work this paper cites.
Convergence analysis of a proximal-like minimization algorithm using Bregman functions
Chen, Gong, Marc Teboulle. 1993 · 1993
Earlier work this paper cites.
Gambling in a rigged casino: The adversarial multi-armed bandit problem
Auer, Peter, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire. 1995 · 1995
Earlier work this paper cites.
Free-steering relaxation methods for problems with strictly convex costs and linear constraints
Kiwiel, Krzysztof C. 1997 · 1997
Earlier work this paper cites.
Online learning and stochastic approximations
Bottou, Léon. 1998 · 1998
Earlier work this paper cites.
Adaptive game playing using multiplicative weights
Freund, Yoav, Robert E. Schapire. 1999 · 1999
Earlier work this paper cites.
Finite-Dimensional Variational Inequalities and Complementarity Problems
Facchinei, Francisco, Jong-Shi Pang. 2003 · 2003
Earlier work this paper cites.
Prox-method with rate of convergence O ( 1 / t ) {O}(1/t) for variational inequalities with Lipschitz continuous monotone operators and smooth convex-concave saddle point problems
Nemirovski, Arkadi Semen. 2004 · 2004
Earlier work this paper cites.
Dual extrapolation and its applications to solving variational inequalities and related problems
Nesterov, Yurii. 2007 · 2007
Earlier work this paper cites.
Robust stochastic approximation approach to stochastic programming
Nemirovski, Arkadi Semen, Anatoli Juditsky, Guanghui Lan, Alexander Shapiro. 2009 · 2009
Earlier work this paper cites.
Solving variational inequalities with stochastic mirror-prox algorithm
Juditsky, Anatoli, Arkadi Semen Nemirovski, Claire Tauvel. 2011 · 2011
Earlier work this paper cites.
Online learning and online convex optimization
Shalev-Shwartz, Shai. 2011 · 2011
Earlier work this paper cites.
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Arora, Sanjeev, Elad Hazan, Satyen Kale. 2012 · 2012
Cited alongside, same era.
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Cited alongside, same era.
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Tieleman, T., G. Hinton. 2012 · 2012
Cited alongside, same era.
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Cited alongside, same era.
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Goodfellow, Ian, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
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Kingma, Diederik, Jimmy Ba. 2014 · 2014
Cited alongside, same era.
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Later among the works it cites.
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Bauschke, Heinz H., Patrick L. Combettes. 2017 · 2017
Later among the works it cites.
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Ge, Rong, Chi Jin, Yi Zheng. 2017 · 2017
Later among the works it cites.
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Later among the works it cites.
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