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A new quasi-Newton method based on adjoint Broyden updates for symmetric nonlinear equations
Huiping Cao 대한수학회 2016 대한수학회지 Vol.53 No.6
In this paper, we propose a new rank two quasi-Newton method based on adjoint Broyden updates for solving symmetric nonlinear equations, which can be seen as a class of adjoint BFGS method. The new rank two quasi-Newton update not only can guarantee that $B_{k+1}$ approximates Jacobian $F'(x_{k+1})$ along direction $s_k$ exactly, but also shares some nice properties such as positive definiteness and least change property with BFGS method. Under suitable conditions, the proposed method converges globally and superlinearly. Some preliminary numerical results are reported to show that the proposed method is effective and competitive.
Subspace Clustering Algorithm Based on Multi-rule Constraint
Huiping Li 보안공학연구지원센터 2014 International Journal of Multimedia and Ubiquitous Vol.9 No.12
For the fact that telecom data size is extremely huge and the management is much complicated, the paper proposes subspace clustering algorithm based on multi-rule constraint, to mine business knowledge information in a more efficient and accurate manner. By relying on K-means clustering algorithm, the method improves selection and mutation operation of genetic algorithms and thus corrects inappropriate choice of K-means initial clustering centers. Meanwhile, with the use of variable weighting strategy, data classification sparseness in the clustering is overcome. A fast and useful mining method is enabled for massive data. Results show its better performance in terms of computing efficiency, accuracy and ability.