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Supported by the recent contributions in multiple branches, the first-order splitting algorithms became central for structured nonsmooth optimization.
On the interchange of subdifferentiation and conditional expectation for convex functionals
R.T. Rockafellar and R.J.-B. Wets · 1982
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Convex Analysis
R.T. Rockafellar · 1988
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Strong conical hull intersection property, bounded linear regularity, jameson’s property (g), and error bounds in convex optimization
Heinz H Bauschke, Jonathan M Borwein, and Wu Li · 1999
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Accelerating the convergence of the method of alternating projections
Heinz Bauschke, Frank Deutsch, Hein Hundal, and Sung-Ho Park · 2003
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A fast iterative shrinkage-thresholding algorithm for linear inverse problems
Amir Beck and Marc Teboulle · 2009
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Robust stochastic approximation approach to stochastic programming
Arkadi Nemirovski, Anatoli Juditsky, Guanghui Lan, and Alexander Shapiro · 2009
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Variational analysis, volume 317
R Tyrrell Rockafellar and Roger J-B Wets · 2009
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Sparse and redundant representations: from theory to applications in signal and image processing
Michael Elad · 2010
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Random projection algorithms for convex set intersection problems
Angelia Nedić · 2010
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Non-asymptotic analysis of stochastic approximation algorithms for machine learning
Eric Moulines and Francis R Bach · 2011
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Random algorithms for convex minimization problems
Angelia Nedić · 2011
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Pegasos: Primal estimated sub-gradient solver for svm
Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro, and Andrew Cotter · 2011
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Regularized iterative stochastic approximation methods for stochastic variational inequality problems
Jayash Koshal, Angelia Nedic, and Uday V Shanbhag · 2012
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Gradient methods for minimizing composite functions
Yu Nesterov · 2013
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Introductory lectures on convex optimization: A basic course, volume 87
Yurii Nesterov · 2013
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Accelerated stochastic gradient method for composite regularization
Wenliang Zhong and James Kwok · 2014
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Network lasso: Clustering and optimization in large graphs
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Andrei Patrascu and Ion Necoara · 2017
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Inexact proximal stochastic gradient method for convex composite optimization
Xiao Wang, Shuxiong Wang, and Hongchao Zhang · 2017
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Sgd and hogwild! convergence without the bounded gradients assumption
Lam M Nguyen, Phuong Ha Nguyen, Marten van Dijk, Peter Richtárik, Katya Scheinberg, and Martin Takáč · 2018
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Stochastic (approximate) proximal point methods: Convergence, optimality, and adaptivity
Hilal Asi and John C Duchi · 2019
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David Hallac, Jure Leskovec, and Stephen Boyd · 2015
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A proximal gradient algorithm for decentralized composite optimization
Wei Shi, Qing Ling, Gang Wu, and Wotao Yin · 2015
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Ergodic convergence of a stochastic proximal point algorithm
Pascal Bianchi · 2016
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Stochastic proximal iteration: a non-asymptotic improvement upon stochastic gradient descent
Ernest K Ryu and Stephen Boyd · 2016
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Towards stability and optimality in stochastic gradient descent
Panos Toulis, Dustin Tran, and Edo Airoldi · 2016
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Stochastic first-order methods with random constraint projection
Mengdi Wang and Dimitri P Bertsekas · 2016
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Damek Davis and Dmitriy Drusvyatskiy · 2019
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Convergence of stochastic proximal gradient algorithm
Lorenzo Rosasco, Silvia Villa, and Bang Công Vũ · 2019
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Snake: a stochastic proximal gradient algorithm for regularized problems over large graphs
Adil Salim, Pascal Bianchi, and Walid Hachem · 2019
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Rohan Varma, Harlin Lee, Jelena Kovacevic, and Yuejie Chi · 2019
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New nonasymptotic convergence rates of stochastic proximal point algorithm for stochastic convex optimization
Andrei Pătraşcu · 2020
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