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关于线性矩阵方程通解的求法 被引量:1
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作者 郑华盛 《工科数学》 2002年第3期83-86,共4页
给出了求线性矩阵方程 Am× n Xn× s=Bm×
关键词 线性矩阵方程 通解 特解矩阵 初等行变换
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矩阵方程解的存在性 被引量:1
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作者 赵翠琴 《洛阳师范学院学报》 2004年第2期27-28,共2页
指出矩阵方程Am×nXn× 1=Bm× 1与矩阵方程Am×nXn×s=Bm×s的解之间的关系 ;然后给出矩阵方程Am×nXn×s=Bm×s解的存在性定理并给出求其通解的方法 .
关键词 矩阵方程 初等行变换 基解矩阵 特解矩阵
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A Robust Collaborative Recommendation Algorithm Based on k-distance and Tukey M-estimator 被引量:6
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作者 YI Huawei ZHANG Fuzhi LAN Jie 《China Communications》 SCIE CSCD 2014年第9期112-123,共12页
The existing collaborative recommendation algorithms have lower robustness against shilling attacks.With this problem in mind,in this paper we propose a robust collaborative recommendation algorithm based on k-distanc... The existing collaborative recommendation algorithms have lower robustness against shilling attacks.With this problem in mind,in this paper we propose a robust collaborative recommendation algorithm based on k-distance and Tukey M-estimator.Firstly,we propose a k-distancebased method to compute user suspicion degree(USD).The reliable neighbor model can be constructed through incorporating the user suspicion degree into user neighbor model.The influence of attack profiles on the recommendation results is reduced through adjusting similarities among users.Then,Tukey M-estimator is introduced to construct robust matrix factorization model,which can realize the robust estimation of user feature matrix and item feature matrix and reduce the influence of attack profiles on item feature matrix.Finally,a robust collaborative recommendation algorithm is devised by combining the reliable neighbor model and robust matrix factorization model.Experimental results show that the proposed algorithm outperforms the existing methods in terms of both recommendation accuracy and robustness. 展开更多
关键词 shilling attacks robust collaborative recommendation matrix factori-zation k-distance Tukey M-estimator
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Note on Implementation of Three-Qubit SWAP Gate
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作者 魏海瑞 狄尧民 +1 位作者 王艳 张洁 《Communications in Theoretical Physics》 SCIE CAS CSCD 2010年第1期78-82,共5页
In this paper, the synthesis and implementation of three-qubit SWAP gate is discussed. The three-qubit SWAP gate can be decomposed into product of 2 two-qubit SWAP gates, and it can be realized by 6 CNOT gates. Resear... In this paper, the synthesis and implementation of three-qubit SWAP gate is discussed. The three-qubit SWAP gate can be decomposed into product of 2 two-qubit SWAP gates, and it can be realized by 6 CNOT gates. Research illustrated that although the result is very simple, the current methods of matrix decomposition for multi-qubit gate can not get that. Then the implementation of three-qubit SWAP gate in the three spin system with Ising interaction is investigated and the sequence of control pulse and drift process to implement the gate is given. It needs 23 control pulses and 12 drift processes. Since the interaction can not be switched on and off at will, the realization of three-qubit SWAP gate in specific quantum system also can not simply come down to 2 two-qubit SWAP gates. 展开更多
关键词 three-qubit SWAP gate matrix decomposition three spin system Ising interaction
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Applications of gauge duality in robust principal component analysis and semidefinite programming
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作者 MA ShiQian YANG JunFeng 《Science China Mathematics》 SCIE CSCD 2016年第8期1579-1592,共14页
Gauge duality theory was originated by Preund (1987), and was recently further investigated by Friedlander et al. (2014). When solving some matrix optimization problems via gauge dual, one is usually able to avoid... Gauge duality theory was originated by Preund (1987), and was recently further investigated by Friedlander et al. (2014). When solving some matrix optimization problems via gauge dual, one is usually able to avoid full matrix decompositions such as singular value and/or eigenvalue decompositions. In such an approach, a gauge dual problem is solved in the first stage, and then an optimal solution to the primal problem can be recovered from the dual optimal solution obtained in the first stage. Recently, this theory has been applied to a class of semidefinite programming (SDP) problems with promising numerical results by Friedlander and Mac^to (2016). We establish some theoretical results on applying the gauge duality theory to robust principal component analysis (PCA) and general SDP. For each problem, we present its gauge dual problem, characterize the optimality conditions for the primal-dual gauge pair, and validate a way to recover a primal optimal solution from a dual one. These results are extensions of Friedlander and Macedo (2016) from nuclear norm regularization to robust PCA and from a special class of SDP which requires the coefficient matrix in the linear objective to be positive definite to SDP problems without this restriction. Our results provide further understanding in the potential advantages and disadvantages of the gauge duality theory. 展开更多
关键词 gauge optimization gauge duality polar function antipolar set singular value decomposition robust principal component analysis semidefinite programming
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