Fetching the paper…
Reading the bibliography…
In this paper, we consider the linearly constrained composite convex optimization problem, whose objective is a sum of a smooth function and a possibly nonsmooth function.
An algorithm for quadratic programming
Marguerite Frank and Philip Wolfe · 1956
Earlier work this paper cites.
Multiplier and gradient methods
Magnus R. Hestenes · 1969
Earlier work this paper cites.
A method for nonlinear constraints in minimization problems
M. J. D. Powell · 1969
Earlier work this paper cites.
Dual algorithms for constrained optimization problems
J. D. Buys · 1972
Earlier work this paper cites.
The multiplier method of Hestenes and Powell applied to convex programming
Ralph Tyrrell Rockafellar · 1973
Earlier work this paper cites.
Newton’s method for problems with equality constraints
R. A. Tapia · 1974
Earlier work this paper cites.
Augmented Lagrangian and applications of the proximal point algorithm in convex progremming
Ralph Tyrrell Rockafellar · 1976
Earlier work this paper cites.
A method of solving a convex programming problem with convergence rate O ( 1 / k 2 ) {O}(1/k^{2})
Yurii Nesterov · 1983
Earlier work this paper cites.
Error bounds and convergence analysis of feasible descent methods: A general approach
Zhi-Quan Luo and Paul Tseng · 1993
Earlier work this paper cites.
Convergence rate analysis of nonquadratic proximal methods for convex and linear programming
Alfredo N. Iusem and Marc Teboulle · 1995
Earlier work this paper cites.
Constrained Optimization and Lagrange Multiplier Methods
Dimitri P. Bertsekas · 1996
Earlier work this paper cites.
Nonlinear Programming
Dimitri P. Bertsekas · 1999
Earlier work this paper cites.
Gradient convergence in gradient methods with errors
Dimitri P. Bertsekas and John N. Tsitsiklis · 2000
Earlier work this paper cites.
Smooth minimization of non-smooth functions
Yurii Nesterov · 2005
Cited alongside, same era.
An iterative regularization method for total variation-based image restoration
Stanley Osher, Martin Burger, Donald Goldfarb, Jinjun Xu, and Wotao Yin · 2005
Cited alongside, same era.
Bregman iterative algorithms for ℓ 1 \ell_{1} -minimization with applications to compressed sensing
Wotao Yin, Stanley Osher, Donald Goldfarb, and Jerome Darbon · 2008
Cited alongside, same era.
A fast iterative shrinkage-thresholding algorithm for linear inverse problems
Amir Beck and Marc Teboulle · 2009
Cited alongside, same era.
The split Bregman method for L1-regularized problems
Tom Goldstein and Stanley Osher · 2009
Cited alongside, same era.
Sparse Convex Optimization Methods for Machine Learning
Martin Jaggi · 2011
Analysis on a superlinearly convergent augmented Lagrangian method
Yaxiang Yuan · 2014
Later among the works it cites.
Conditional gradient algorithms for norm-regularized smooth convex optimization
Zaid Harchaoui, Anatoli Juditsky, and Arkadi Nemirovski · 2015
Later among the works it cites.
SDPNAL+: A majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints
Liuqin Yang, Defeng Sun, and Kim-Chuan Toh · 2015
Later among the works it cites.
Gradient sliding for composite optimization
Guanghui Lan · 2016
Closest in time.
Iteration-complexity of first-order augmented Lagrangian methods for convex programming
Guanghui Lan and Renato D. C. Monteiro · 2016
Closest in time.
Conditional gradient sliding for convex optimization
Guanghui Lan and Yi Zhou · 2016
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
A practical relative error criterion for augmented Lagrangians
Jonathan Eckstein and Paulo J. S. Silva · 2013
Cited alongside, same era.
Revisiting Frank-Wolfe: Projection-free sparse convex optimization
Martin Jaggi · 2013
Cited alongside, same era.
An efficient augmented Lagrangian method with applications to total variation minimization
Chengbo Li, Wotao Yin, Hong Jiang, and Yin Zhang · 2013
Cited alongside, same era.
Gradient methods for minimizing composite functions
Yurii Nesterov · 2013
Cited alongside, same era.
Error forgetting of Bregman iteration
Wotao Yin and Stanley Osher · 2013
Cited alongside, same era.
First-order methods of smooth convex optimization with inexact oracle
Olivier Devolder, François Glineur, and Yurii Nesterov · 2014
Cited alongside, same era.
Closest in time.
Scalable robust matrix recovery: Frank–Wolfe meets proximal methods
Cun Mu, Yuqian Zhang, John Wright, and Donald Goldfarb · 2016
Closest in time.
Iteration complexity analysis of dual first-order methods for conic convex programming
Ion Necoara and Andrei Patrascu · 2016
Closest in time.
Complexity of first order inexact Lagrangian and penalty methods for conic convex programming
Ion Necoara, Andrei Patrascu, and Francois Glineur · 2017
Closest in time.
Complexity bounds for primal-dual methods minimizing the model of objective function
Yurri Nesterov · 2017
Closest in time.
Non-asymptotic convergence analysis of inexact gradient methods for machine learning without strong convexity
Anthony Man-Cho So and Zirui Zhou · 2017
Closest in time.
A highly efficient semismooth Newton augmented Lagrangian method for solving Lasso problems
Xudong Li, Defeng Sun, and Kim-Chuan Toh · 2018
Closest in time.