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The alternating direction method of multipliers (ADMM) is commonly used for distributed model fitting problems, but its performance and reliability depend strongly on user-defined penalty parameters.
Convex Analysis
Rockafellar, R · 1970
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Sur l’approximation, par éléments finis d’ordre un, et la résolution, par pénalisation-dualité d’une classe de problémes de Dirichlet non linéaires
Glowinski, Roland and Marroco, A · 1975
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A dual algorithm for the solution of nonlinear variational problems via finite element approximation
Gabay, Daniel and Mercier, Bertrand · 1976
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On the limited memory bfgs method for large scale optimization
Liu, Dong C and Nocedal, Jorge · 1989
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On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators
Eckstein, Jonathan and Bertsekas, Dimitri · 1992
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Gradient-based learning applied to document recognition
LeCun, Yann, Bottou, Léon, Bengio, Yoshua, and Haffner, Patrick · 1998
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Alternating direction method with self-adaptive penalty parameters for monotone variational inequalities
He, Bingsheng, Yang, Hai, and Wang, Shengli · 2000
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A nonlinear programming algorithm for solving semidefinite programs via low-rank factorization
Burer, Samuel and Monteiro, Renato DC · 2003
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Regularization and variable selection via the elastic net
Zou, Hui and Hastie, Trevor · 2005
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Gradient methods with adaptive step-sizes
Zhou, Bin, Gao, Li, and Dai, Yu-Hong · 2006
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Learning multiple layers of features from tiny images
Krizhevsky, Alex and Hinton, Geoffrey · 2009
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Large-scale sparse logistic regression
Liu, Jun, Chen, Jianhui, and Ye, Jieping · 2009
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High-order methods for basis pursuit
Goldstein, Tom and Setzer, Simon · 2010
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Distributed optimization and statistical learning via the alternating direction method of multipliers
Boyd, Stephen, Parikh, Neal, Chu, Eric, Peleato, Borja, and Eckstein, Jonathan · 2011
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LIBSVM: a library for support vector machines
Chang, Chih-Chung and Lin, Chih-Jen · 2011
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Linearized alternating direction method with adaptive penalty for low-rank representation
Lin, Zhouchen, Liu, Risheng, and Su, Zhixun · 2011
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On the o(1/n) convergence rate of the douglas-rachford alternating direction method
He, Bingsheng and Yuan, Xiaoming · 2012
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Fast alternating linearization methods for minimizing the sum of two convex functions
Goldfarb, Donald, Ma, Shiqian, and Scheinberg, Katya · 2013
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Stochastic alternating direction method of multipliers
Adaptive primal-dual splitting methods for statistical learning and image processing
Goldstein, Tom, Li, Min, and Yuan, Xiaoming · 2015
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On non-ergodic convergence rate of Douglas-Rachford alternating direction method of multipliers
He, Bingsheng and Yuan, Xiaoming · 2015
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Accelerated alternating direction method of multipliers
Kadkhodaie, Mojtaba, Christakopoulou, Konstantina, Sanjabi, Maziar, and Banerjee, Arindam · 2015
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A general analysis of the convergence of ADMM
Nishihara, R., Lessard, L., Recht, B., Packard, A., and Jordan, M · 2015
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Fixing and extending some recent results on the admm algorithm
Banert, Sebastian, Bot, Radu Ioan, and Csetnek, Ernö Robert · 2016
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Ouyang, Hua, He, Niao, Tran, Long, and Gray, Alexander G · 2013
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Faster convergence rates of relaxed peaceman-rachford and admm under regularity assumptions
Davis, Damek and Yin, Wotao · 2014
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Fast alternating direction optimization methods
Goldstein, Tom, O’Donoghue, Brendan, Setzer, Simon, and Baraniuk, Richard · 2014
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Alternating direction method of multipliers for strictly convex quadratic programs: Optimal parameter selection
Raghunathan, Arvind and Di Cairano, Stefano · 2014
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Studer, Christoph, Goldstein, Tom, Yin, Wotao, and Baraniuk, Richard G · 2014
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Asynchronous distributed ADMM for consensus optimization
Zhang, Ruiliang and Kwok, James T · 2014
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Optimal parameter selection for the alternating direction method of multipliers: quadratic problems
Ghadimi, Euhanna, Teixeira, André, Shames, Iman, and Johansson, Mikael · 2015
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Asynchronous distributed alternating direction method of multipliers: Algorithm and convergence analysis
Chang, Tsung-Hui, Hong, Mingyi, Liao, Wei-Cheng, and Wang, Xiangfeng · 2016
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An explicit rate bound for over-relaxed admm
França, Guilherme and Bento, José · 2016
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Linear convergence and metric selection in douglas-rachford splitting and admm
Giselsson, Pontus and Boyd, Stephen · 2016
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Unwrapping ADMM: efficient distributed computing via transpose reduction
Goldstein, Tom, Taylor, Gavin, Barabin, Kawika, and Sayre, Kent · 2016
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Fast ADMM algorithm for distributed optimization with adaptive penalty
Song, Changkyu, Yoon, Sejong, and Pavlovic, Vladimir · 2016
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Training neural networks without gradients: A scalable ADMM approach
Taylor, Gavin, Burmeister, Ryan, Xu, Zheng, Singh, Bharat, Patel, Ankit, and Goldstein, Tom · 2016
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Faster alternating direction method of multipliers with a worst-case o (1/ n 2 n^{2} ) convergence rate
Tian, Wenyi and Yuan, Xiaoming · 2016
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