@article{d843097c88b348d781658060cf9da569,
title = "Rate of convergence analysis of dual-based variables decomposition methods for strongly convex problems",
abstract = "We consider the problem of minimizing the sum of a strongly convex function and a term comprising the sum of extended real-valued proper closed convex functions. We derive the primal representation of dual-based block descent methods and establish a relation between primal and dual rates of convergence, allowing to compute the efficiency estimates of different methods. We illustrate the effectiveness of the methods by numerical experiments on total variation-based denoising problems.",
keywords = "Block variables decomposition, Dual based methods, Total variation denoising",
author = "Amir Beck and Luba Tetruashvili and Yakov Vaisbourd and Ariel Shemtov",
note = "Publisher Copyright: {\textcopyright} 2015 Elsevier B.V.",
year = "2016",
month = jan,
doi = "10.1016/j.orl.2015.11.007",
language = "אנגלית",
volume = "44",
pages = "61--66",
journal = "Operations Research Letters",
issn = "0167-6377",
publisher = "Elsevier B.V.",
number = "1",
}