【摘要】：正1引言本文討論的兩個可分離算子的線性約束凸優(yōu)化問題是min{θ_i(x)+θ_2(y)|Ax+By=b,x∈X,y∈y},(1.1)其中A∈R~(m×n_1),B∈R~(m×n_2),b∈R~m;X?R~(n_1),y?R~(n_2)是閉凸集;θ_1(x):R~(n_1)→R和θ_2(y):R~(n_2)→R是(不一定光滑的)凸函數(shù).這類問題大量出現(xiàn)在圖像處理,機器學習等稀疏優(yōu)化領(lǐng)域[2].乘子交替方向法(Alternating Directions Method of Multipliers),簡稱ADMM,通常稱之為交替方向法,最初由Glowinski等為偏微分方程數(shù)值求解在[7,8],中
[Abstract]:The linear constrained convex optimization problem of two separable operators discussed in this paper is min {胃 I (x) 胃 2 (y) Ax Bybn x 鈭，

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