Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Xuewen Mu"'
Autor:
Yaling Zhang, Xuewen Mu
Publikováno v:
Journal of Inequalities and Applications, Vol 2023, Iss 1, Pp 1-15 (2023)
Abstract In this paper, we present an inexact multiblock alternating direction method for the point-contact friction model of the force-optimization problem (FOP). The friction-cone constraints of the FOP are reformulated as the Cartesian product of
Externí odkaz:
https://doaj.org/article/b2c8e865c5a14c25a6421d497152c06e
Autor:
Xuewen Mu, Yaling Zhang
Publikováno v:
Journal of Applied Mathematics, Vol 2013 (2013)
Based on the semidefinite programming relaxation of the binary quadratic programming, a rank-two feasible direction algorithm is presented. The proposed algorithm restricts the rank of matrix variable to be two in the semidefinite programming relaxat
Externí odkaz:
https://doaj.org/article/69c4e44ad00f4ee2a73455d28fb2c06a
Autor:
Yitong Liu1 ytliu613@stu.xidian.edu.cn, Xuewen Mu1
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 2023, Vol. 44 Issue 1, p1257-1268. 12p.
Publikováno v:
Computers, Materials & Continua; 2024, Vol. 79 Issue 1, p695-712, 18p
Publikováno v:
Frontiers of Chemical Science and Engineering.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cc610d32b20c776d0e886cdc1f4adbe6
https://doi.org/10.1007/s11705-022-2194-7
https://doi.org/10.1007/s11705-022-2194-7
Publikováno v:
Applied Numerical Mathematics. 165:1-21
In this paper, we first study a relaxed inertial projection and contraction method for variational inequalities to obtain weak convergence results under standard assumptions in Hilbert spaces. Next, we propose another inertial projection and contract
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5178989fe8a435a5d5c64c39b5d31a04
https://doi.org/10.1016/j.apnum.2021.02.004
https://doi.org/10.1016/j.apnum.2021.02.004
Autor:
Xuewen Mu, Guishan Dong
Publikováno v:
International Journal of Machine Learning and Cybernetics. 12:2733-2746
The second-order cone programming support vector machine (SOCP-SVM) formulations have received much attention as the robust and efficient framework for classification. In this paper, we formulate the SOCP-SVM as the convex quadratic circular cone pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c638af1d94b3ab03f56bdb3e1f00ea7c
https://doi.org/10.1007/s13042-021-01360-2
https://doi.org/10.1007/s13042-021-01360-2
Autor:
Xuewen Mu, Guishan Dong
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 39:4505-4513
The support vector machine is a classification approach in machine learning. The second-order cone optimization formulation for the soft-margin support vector machine can ensure that the misclassification rate of data points do not exceed a given val
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b87ad7b8a3809ad87ff0ba91a3a5db9
https://doi.org/10.3233/jifs-200467
https://doi.org/10.3233/jifs-200467
Autor:
Xuewen Mu, Yaling Zhang
Publikováno v:
Journal of Optimization Theory and Applications. 183:592-608
Grasping force optimization of multi-fingered robotic hands can be formulated as a convex quadratic circular cone programming problem, which consists in minimizing a convex quadratic objective function subject to the friction cone constraints and bal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6e9bf5efb75e131852194ed9a5a2fe9
https://doi.org/10.1007/s10957-019-01540-9
https://doi.org/10.1007/s10957-019-01540-9
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 35:1979-1990
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e29f786b32409f535a98975bf960fc12
https://doi.org/10.3233/jifs-171643
https://doi.org/10.3233/jifs-171643