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We present a stochastic setting for optimization problems with nonsmooth convex separable objective functions over linear equality constraints.
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“The split bregman method for l1-regularized problems,”
Tom Goldstein and Stanley Osher, · 2009
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“A unified primal-dual algorithm framework based on bregman iteration,”
Xiaoqun Zhang, Martin Burger, and Stanley Osher, · 2011
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“On the o ( 1 / n ) o(1/n) convergence rate of the douglas-rachford alternating direction method,”
Bingsheng He and Xiaoming Yuan, · 2012
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“On non-ergodic convergence rate of douglas-rachford alternating direction method of multipliers,”
Bingsheng He and Xiaoming Yuan, · 2012
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“Online alternating direction method,”
Huahua Wang and Arindam Banerjee, · 2012
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“Linearized augmented lagrangian and alternating direction methods for nuclear norm minimization,”
Junfeng Yang and Xiaoming Yuan, · 2012
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“Alternating direction algorithms for ℓ 1 \ell_{1} -problems in compressive sensing,”
Junfeng Yang and Yin Zhang, · 2011
Cited alongside, same era.