This paper develops a general theoretical framework to analyze structured
sparse recovery problems using the notation of dual certificate. Although
certain aspects of the dual certificate idea have already been used in some
previous work, due to the lack of a general and coherent theory, the analysis
has so far only been carried out in limited scopes for specific problems. In
this context the current paper makes two contributions. First, we introduce a
general definition of dual certificate, which we then use to develop a unified
theory of sparse recovery analysis for convex programming. Second, we present a
class of structured sparsity regularization called structured Lasso for which
calculations can be readily performed under our theoretical framework. This new
theory includes many seemingly loosely related previous work as special cases;
it also implies new results that improve existing ones even for standard
formulations such as L1 regularization