A MEMORYLESS SYMMETRIC RANK-ONE METHOD WITH SUFFICIENT DESCENT PROPERTY FOR UNCONSTRAINED OPTIMIZATION
Author:
Affiliation:
1. Tokyo University of Science
2. Yokohama National University
Publisher
The Operations Research Society of Japan
Subject
Management Science and Operations Research,General Decision Sciences
Link
https://www.jstage.jst.go.jp/article/jorsj/61/1/61_53/_pdf
Reference33 articles.
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3. [3] H. Byrd, F. Khalfan, and B. Schnabel: Analysis of a symmetric rank-one trust region method. SIAM Journal on Optimization, 6 (1996), 1025–1039.
4. [4] W.Y. Cheng and D.H. Li: Spectral scaling BFGS method. Journal of Optimization Theory and Applications, 146 (2010), 305–319.
5. [5] A.R. Conn, N.I.M. Gould, and Ph.L. Toint: Convergence of quasi-Newton matrices generated by the symmetric rank one update. Mathematical Programming, 50 (1991), 177–195.
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1. A hybrid method of three-term conjugate gradient method and memoryless quasi-Newton method for unconstrained optimization;SUT Journal of Mathematics;2018-06-01
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