Lu, Yue; Liu, Xiao Lavrentiev regularization method in rank learning. (Chinese. English summary) Zbl 1424.68125 J. Fudan Univ., Nat. Sci. 57, No. 6, 706-717, 724 (2018). Summary: This paper studies the convergence of Lavrentiev regularization method in ranking learning. To solve the pairwise ranking problem, the main existing method is to solve a minimization problem with Tikhonov regularization. However, applying the self conjugation operator with the standard Tikhonov regularization scheme can be transformed into a form of that with Lavrentiev regularization scheme. Moreover, the convergence order of this Lavrentiev sorting algorithm under a certain smoothness condition is obtained through a convergence analysis of the method. MSC: 68T05 Learning and adaptive systems in artificial intelligence 65F22 Ill-posedness and regularization problems in numerical linear algebra Keywords:rank learning; regularization method; convergence analysis PDFBibTeX XMLCite \textit{Y. Lu} and \textit{X. Liu}, J. Fudan Univ., Nat. Sci. 57, No. 6, 706--717, 724 (2018; Zbl 1424.68125)