@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",

}