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We consider the audio declipping problem by using iterative thresholding algorithms and the principle of social sparsity. This recently introduced approach features thresholding/shrinkage operators which allow to model dependencies between neighboring coefficients in expansions with time-frequency dictionaries. A new unconstrained convex formulation of the audio declipping problem is introduced. The chosen structured thresholding operators are the so called windowed group-Lasso and thedoi:10.1109/icassp.2014.6853863 dblp:conf/icassp/SiedenburgKD14 fatcat:bc4dv5xszvfw7l3babrjotbelu