Fetching the paper…
Reading the bibliography…
Minimax optimization has become a central tool in machine learning with applications in robust optimization, reinforcement learning, GANs, etc.
On the numerical solution of heat conduction problems in two and three space variables
Jim Douglas and Henry H Rachford · 1956
Earlier work this paper cites.
Monotone operators and the proximal point algorithm
R. Tyrrell Rockafellar · 1976
Earlier work this paper cites.
A convergence for bivariate functions aimed at the convergence of saddle values
Hedy Attouch and Roger J.-B. Wets · 1983
Earlier work this paper cites.
A convergence theory for saddle functions
Hedy Attouch and Roger J.-B. Wets · 1983
Earlier work this paper cites.
Maximal monotone relations and the second derivatives of nonsmooth functions
R. Tyrrell Rockafellar · 1985
Earlier work this paper cites.
On continuity properties of the partial legendre-fenchel transform: Convergence of sequences of augmented lagrangian functions, moreau-yosida approximates and subdifferential operators
Hedy Attouch, Dominique Aze, and Roger J.-B. Wets · 1986
Earlier work this paper cites.
On penalty methods for minimax problems
Sjur Didrik Flam · 1986
Earlier work this paper cites.
Rate of convergence for the saddle points of convex-concave functions
Dominique Aze · 1988
Earlier work this paper cites.
Convergence of approximate saddle points
Jean Guillerme · 1989
Earlier work this paper cites.
Variational convergence and perturbed proximal method for saddle point problems
K. Mouallif · 1989
Earlier work this paper cites.
Generalized second derivatives of convex functions and saddle functions
R. Tyrrell Rockafellar · 1990
Earlier work this paper cites.
On the douglas—rachford splitting method and the proximal point algorithm for maximal monotone operators
Jonathan Eckstein and Dimitri P Bertsekas · 1992
Earlier work this paper cites.
On linear convergence of iterative methods for the variational inequality problem
Paul Tseng · 1995
Earlier work this paper cites.
Prox-method with rate of convergence o (1/t) for variational inequalities with lipschitz continuous monotone operators and smooth convex-concave saddle point problems
Arkadi Nemirovski · 2004
Earlier work this paper cites.
Smooth minimization of non-smooth functions
Yu Nesterov · 2005
Cited alongside, same era.
A first-order primal-dual algorithm for convex problems with applications to imaging
Antonin Chambolle and Thomas Pock · 2011
Cited alongside, same era.
Generative adversarial nets
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Cited alongside, same era.
Gradient descent only converges to minimizers
Jason D Lee, Max Simchowitz, Michael I Jordan, and Benjamin Recht · 2016
Cited alongside, same era.
Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2017
Cited alongside, same era.
Stochastic mirror descent in variationally coherent optimization problems
Minmax optimization: Stable limit points of gradient descent ascent are locally optimal
Chi Jin, Praneeth Netrapalli, and Michael I. Jordan · 2019
Later among the works it cites.
On gradient descent ascent for nonconvex-concave minimax problems
Tianyi Lin, Chi Jin, and Michael I. Jordan · 2019
Later among the works it cites.
Aryan Mokhtari, Asuman Ozdaglar, and Sarath Pattathil · 2019
Later among the works it cites.
Solving a class of non-convex min-max games using iterative first order methods
Maher Nouiehed, Maziar Sanjabi, Tianjian Huang, Jason D Lee, and Meisam Razaviyayn · 2019
Later among the works it cites.
Efficient algorithms for smooth minimax optimization
Kiran K Thekumparampil, Prateek Jain, Praneeth Netrapalli, and Sewoong Oh · 2019
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Stephen Boyd, and Peter W Glynn · 2017
Cited alongside, same era.
Boosting the actor with dual critic
Bo Dai, Albert Shaw, Niao He, Lihong Li, and Le Song · 2018
Cited alongside, same era.
The limit points of (optimistic) gradient descent in min-max optimization
Constantinos Daskalakis and Ioannis Panageas · 2018
Cited alongside, same era.
Qihang Lin, Mingrui Liu, Hassan Rafique, and Tianbao Yang · 2018
Cited alongside, same era.
Non-convex min-max optimization: Provable algorithms and applications in machine learning
Hassan Rafique, Mingrui Liu, Qihang Lin, and Tianbao Yang · 2018
Cited alongside, same era.
Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
Cited alongside, same era.
On the convergence rate of stochastic mirror descent for nonsmooth nonconvex optimization
Siqi Zhang and Niao He · 2018
Cited alongside, same era.
Later among the works it cites.
Do gans always have nash equilibria?
Farzan Farnia and Asuman Ozdaglar · 2020
Closest in time.
The landscape of nonconvex-nonconcave minimax optimization
Benjamin Grimmer, Haihao Lu, Pratik Worah, and Vahab Mirrokni · 2020
Closest in time.
Limiting behaviors of nonconvex-nonconcave minimax optimization via continuous-time systems
Benjamin Grimmer, Haihao Lu, Pratik Worah, and Vahab Mirrokni · 2020
Closest in time.
The limits of min-max optimization algorithms: convergence to spurious non-critical sets
Ya-Ping Hsieh, Panayotis Mertikopoulos, and Volkan Cevher · 2020
Closest in time.
On the impossibility of global convergence in multi-loss optimization
Alistair Letcher · 2020
Closest in time.
Near-optimal algorithms for minimax optimization
Tianyi Lin, Chi Jin, and Michael I. Jordan · 2020
Closest in time.
Junchi Yang, Negar Kiyavash, and Niao He · 2020
Closest in time.
Optimality and stability in non-convex-non-concave min-max optimization
Guojun Zhang, Pascal Poupart, and Yaoliang Yu · 2020
Closest in time.
Efficient methods for structured nonconvex-nonconcave min-max optimization
Jelena Diakonikolas, Constantinos Daskalakis, and Michael Jordan · 2021
Closest in time.