An Accelerated Proximal Extragradient Method with Applications in Representative Selection. Issue 1 (1st April 2022) - Fang, Changjie; He, Liangsong
Abstract: Proximal algorithms has the advantages of low iteration cost and fast convergence speed, and is a common method for dealing with sparse structures. In this paper, we present an accelerated proximal extra-gradient method for figuring out the representative selection problems. We proved the convergence of the algorithm we proposed. Moreover, we apply our method to solve representative selection problem. Numerical experiments illustrate the advantages of our method.