Proximal Minimization Methods with Generalized Bregman Functions 论文
1997SIAM Journal on Control and Optimization引用 241
Optimization and Variational AnalysisAdvanced Optimization Algorithms ResearchSparse and Compressive Sensing Techniques
摘要
We consider methods for minimizing a convex function f that generate a sequence {xk} by taking xk+1 to be an approximate minimizer of f(x)+Dh(x,xk)/ck, where ck > 0 and Dh is the D-function of a Bregman function h. Extensions are made to B-functions that generalize Bregman functions and cover more applications. Convergence is established under criteria amenable to implementation. Applications are made to nonquadratic multiplier methods for nonlinear programs.