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In this paper, we develop two new randomized block-coordinate optimistic gradient algorithms to approximate a solution of nonlinear equations in large-scale settings, which are called root-finding problems.
Rahimian H, Mehrotra S (2019) Distributionally robust optimization: A review
1908
Earlier work this paper cites.
Halpern B (1967) Fixed points of nonexpanding maps
1967
Earlier work this paper cites.
Auslender A (1971) Méthodes numériques pour la décomposition et la minimisation de fonctions non différentiables
1971
Earlier work this paper cites.
Robbins H, Siegmund D (1971) A convergence theorem for non negative almost supermartingales and some applications
1971
Earlier work this paper cites.
Korpelevich G (1976) The extragradient method for finding saddle points and other problems
1976
Earlier work this paper cites.
Rockafellar R (1976) Monotone operators and the proximal point algorithm
1976
Earlier work this paper cites.
Lions PL, Mercier B (1979) Splitting algorithms for the sum of two nonlinear operators
1979
Earlier work this paper cites.
Popov LD (1980) A modification of the Arrow-Hurwicz method for search of saddle points
1980
Earlier work this paper cites.
Nesterov Y (1983) A method for unconstrained convex minimization problem with the rate of convergence
1983
Earlier work this paper cites.
Bertsekas D, Tsitsiklis JN (1989)
1989
Earlier work this paper cites.
Luo ZQ, Tseng P (1993) Error bounds and convergence analysis of feasible descent methods: a general approach
1993
Earlier work this paper cites.
Kuhn HW, Harsanyi J, Selten R, Weibul J, van Damme E (1996) The work of John nash in game theory
1996
Earlier work this paper cites.
Ortega JM, Rheinboldt WC (2000)
2000
Earlier work this paper cites.
Tseng P (2000) A modified forward-backward splitting method for maximal monotone mappings
2000
Earlier work this paper cites.
Agarwal RP, Meehan M, O’regan D (2001)
2001
Earlier work this paper cites.
Ben-Tal A, Margalit T, Nemirovski A (2001) The ordered subsets mirror descent optimization method with applications to tomography
2001
Earlier work this paper cites.
Konnov I (2001)
2001
Earlier work this paper cites.
Facchinei F, Pang JS (2003)
2003
Earlier work this paper cites.
Nemirovskii A (2004) Prox-method with rate of convergence
2004
Earlier work this paper cites.
Nesterov Y (2004)
2004
Earlier work this paper cites.
Rockafellar R, Wets R (2004)
2004
Earlier work this paper cites.
Combettes PL, Wajs VR (2005) Signal recovery by proximal forward-backward splitting
2005
Earlier work this paper cites.
Nesterov Y (2007) Dual extrapolation and its applications to solving variational inequalities and related problems
2007
Earlier work this paper cites.
Burachik RS, Iusem A (2008)
2008
Earlier work this paper cites.
Ben-Tal A, El Ghaoui L, Nemirovski A (2009)
2009
Earlier work this paper cites.
Nedíc A, Ozdaglar A (2009) Distributed subgradient methods for multi-agent optimization
2009
Earlier work this paper cites.
Phelps RR (2009)
2009
Earlier work this paper cites.
Peypouquet J, Sorin S (2010) Evolution equations for maximal monotone operators: Asymptotic analysis in continuous and discrete time
2010
Earlier work this paper cites.
Chang CC, Lin CJ (2011) LIBSVM: A library for Support Vector Machines
2011
Earlier work this paper cites.
Nesterov Y (2012) Efficiency of coordinate descent methods on huge-scale optimization problems
2012
Earlier work this paper cites.
Sra S, Nowozin S, Wright SJ (2012)
2012
Earlier work this paper cites.
Hsieh CJ, Sustik MA, Dhillon IS, Ravikumar PK, Poldrack R (2013) BIG & QUIC: Sparse inverse covariance estimation for a million variables
2013
Cited alongside, same era.
Defazio A, Bach F, Lacoste-Julien S (2014) SAGA: A fast incremental gradient method with support for non-strongly convex composite objectives
2014
Cited alongside, same era.
Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y (2014) Generative adversarial nets
2014
Cited alongside, same era.
Combettes PL, Pesquet JC (2015) Stochastic quasi-Fejér block-coordinate fixed point iterations with random sweeping
2015
Cited alongside, same era.
Malitsky Y (2015) Projected reflected gradient methods for monotone variational inequalities
2015
Cited alongside, same era.
Lan G (2020)
2020
Later among the works it cites.
Malitsky Y, Tam MK (2020) A forward-backward splitting method for monotone inclusions without cocoercivity
2020
Later among the works it cites.
Martinez N, Bertran M, Sapiro G (2020) Minimax pareto fairness: A multi objective perspective
2020
Later among the works it cites.
Mokhtari A, Ozdaglar A, Pattathil S (2020) A unified analysis of extra-gradient and optimistic gradient methods for saddle point problems: Proximal point approach
2020
Later among the works it cites.
Diakonikolas J, Daskalakis C, Jordan M (2021) Efficient methods for structured nonconvex-nonconcave min-max optimization
2021
Later among the works it cites.
Du W, Xu D, Wu X, Tong H (2021) Fairness-aware agnostic federated learning
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Wright SJ (2015) Coordinate descent algorithms
2015
Cited alongside, same era.
Kim D, Fessler JA (2016) Optimized first-order methods for smooth convex minimization
2016
Cited alongside, same era.
2016
Cited alongside, same era.
Namkoong H, Duchi J (2016) Stochastic gradient methods for distributionally robust optimization with f-divergences
2016
Cited alongside, same era.
Peng Z, Xu Y, Yan M, Yin W (2016) ARock: an algorithmic framework for asynchronous parallel coordinate updates
2016
Cited alongside, same era.
Richtárik P, Takáč M (2016) Parallel coordinate descent methods for big data optimization
2016
Cited alongside, same era.
Ryu EK, Boyd S (2016) Primer on monotone operator methods
2016
Cited alongside, same era.
2021
Later among the works it cites.
Kim D (2021) Accelerated proximal point method for maximally monotone operators
2021
Later among the works it cites.
Lee S, Kim D (2021) Fast extra gradient methods for smooth structured nonconvex-nonconcave minimax problems
2021
Later among the works it cites.
Lieder F (2021) On the convergence rate of the halpern-iteration
2021
Later among the works it cites.
McMahan HB, et al. (2021) Advances and open problems in federated learning
2021
Later among the works it cites.
Ouyang Y, Xu Y (2021) Lower complexity bounds of first-order methods for convex-concave bilinear saddle-point problems
2021
Later among the works it cites.
Tran-Dinh Q, Luo Y (2021) Halpern-type accelerated and splitting algorithms for monotone inclusions
2021
Later among the works it cites.
Tran-Dinh Q, Pham NH, Phan DT, Nguyen LM (2021) FedDR–Randomized Douglas-Rachford splitting algorithms for nonconvex federated composite optimization
2021
Later among the works it cites.
Yoon T, Ryu EK (2021) Accelerated algorithms for smooth convex-concave minimax problems with
2021
Later among the works it cites.
Böhm A (2022) Solving nonconvex-nonconcave min-max problems exhibiting weak Minty solutions
2022
Later among the works it cites.
Davis D (2022) Variance reduction for root-finding problems
2022
Later among the works it cites.
Ho E, Rajagopalan A, Skvortsov A, Arulampalam S, Piraveenan M (2022) Game theory in defence applications: A review
2022
Later among the works it cites.
Maingé PE (2022) Fast convergence of generalized forward-backward algorithms for structured monotone inclusions
2022
Later among the works it cites.
Pethick T, Patrinos P, Fercoq O, Cevher V (2022) Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems
2022
Later among the works it cites.
Ryu E, Yin W (2022)
2022
Later among the works it cites.
Sharma P, Panda R, Joshi G, Varshney P (2022) Federated minimax optimization: Improved convergence analyses and algorithms
2022
Later among the works it cites.
Tarzanagh DA, Li M, Thrampoulidis C, Oymak S (2022) Fednest: Federated bilevel, minimax, and compositional optimization
2022
Later among the works it cites.
Tran-Dinh Q, Liu D (2022) A new randomized primal-dual algorithm for convex optimization with optimal last iterate rates
2022
Later among the works it cites.
Bot RI, Sedlmayer M, Vuong PT (2023) A relaxed inertial forward-backward-forward algorithm for solving monotone inclusions with application to GANs
2023
Closest in time.
Fercoq O, Richtárik P (2015) Accelerated, parallel, and proximal coordinate descent
2023
Closest in time.
Tran-Dinh Q (2023) Extragradient-Type Methods with
2023
Closest in time.
Tran-Dinh Q (2024) From Halpern’s fixed-point iterations to Nesterov’s accelerated interpretations for root-finding problems
2024
Closest in time.
Beck A, Pauwels E, Sabach S (2015) The cyclic block conditional gradient method for convex optimization problems
2049
Closest in time.
Maingé PE (2021) Accelerated proximal algorithms with a correction term for monotone inclusions
2061
Closest in time.
Kotsalis G, Lan G, Li T (2022) Simple and optimal methods for stochastic variational inequalities, i: operator extrapolation
2073
Closest in time.