@article{46289bd73558487f9ed6adb7694656ab,
title = "A first order method for finding minimal norm-like solutions of convex optimization problems",
abstract = "We consider a general class of convex optimization problems in which one seeks to minimize a strongly convex function over a closed and convex set which is by itself an optimal set of another convex problem. We introduce a gradient-based method, called the minimal norm gradient method, for solving this class of problems,and establish the convergence of the sequence generated by the algorithm as well as a rate of convergence of the sequence of function values.",
keywords = "Bilevel optimization, Complexity analysis, Convex minimization, Minimal norm solution",
author = "Amir Beck and Shoham Sabach",
note = "Publisher Copyright: {\textcopyright} 2013,Springer-Verlag Berlin Heidelberg and Mathematical Optimization Society",
year = "2014",
doi = "10.1007/s10107-013-0708-2",
language = "אנגלית",
volume = "147",
pages = "25--46",
journal = "Mathematical Programming",
issn = "0025-5610",
publisher = "Springer-Verlag GmbH and Co. KG",
number = "1",
}