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Contraction Methods for Convex Optimization and Monotone Variational Inequalities – No.17 Alternating direction method with Gaussian back substitution for separable convex optimization Bingsheng He Department of Mathematics Nanjing University

[email protected] The context of this lecture is based on the publication [7]

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1 Introduction In the literature, the alternating direction method (ADM) proposed originally for the following linearly constrained separable convex programming whose objective function is separable into two individual convex functions without crossed variables:

min

θ1 (x1 ) + θ2 (x2 ) A1 x1 + A2 x2 = b,

(1.1)

x1 ∈ X1 and x2 ∈ X2 , :