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| 1 | A Feasible Semismooth Asymptotically Newton Method for Mixed Complementarity Problems 显示文摘 | SUN Defeng Womersley R S Q1 Houduo | 2002 | Math Program2002，94，1： | 1 |
| 2 | Lagrangian duality and saddle points for sparse linear programming显示文摘The sparse linear programming(SLP) is a linear programming problem equipped with a sparsity constraint, which is nonconvex, discontinuous and generally NP-hard due to the combinatorial property involved.In this paper, by rewriting the sparsity constraint into a disjunctive form, we present an explicit formula of the Lagrangian dual problem for the SLP, in terms of an unconstrained piecewise-linear convex programming problem which admits a strong duality under bi-dual sparsity consistency. Furthermore, we show a saddle point theorem based on the strong duality and analyze two classes of stationary points for the saddle point problem. At last,we extend these results to SLP with the lower bound zero replaced by a certain negative constant. | Chen Zhao Ziyan Luo Weiyue Li Houduo Qi Naihua Xiu | 2019 | Science China Mathematics2019，62，10： | 1 |
| 3 | Convergence of Newton smethod for convex best interpolation 显示文摘 | Asen L Dontchev Houduo Qi liqun Qi | 2001 | Num- er Math2001，87，： | 1 |
| 4 | A neural network for the linear complementarity problem显示文摘 | Liao Lizhi Qi Houduo | 1999 | Mathematical and Computer Modelling1999，29，： | 1 |
| 5 | A sequential semismooth Newton method for the nearest low-rank correlation matrix problem显示文摘 | Li Qingna Qi Houduo | | 0，，04： | 1 |
| 6 | Solving nonlinear complementarity problems with neural networks: a reformulation method approach显示文摘 | Liao Lizhi Qi Houduo Qi Liqun | 2001 | Journal of Computational and Applied Mathematics2001，131，： | 1 |
| 7 | Cartesian P-property and Its Applications to the Semidefinite Linear Complementarity Problem显示文摘 | Xin Chen Houduo Qi | 2006 | Mathematical Programming2006，，1： | 1 |
| 8 | AN INEXACT SMOOTHING NEWTON METHOD FOR EUCLIDEAN DISTANCE MATRIX OPTIMIZATION UNDER ORDINAL CONSTRAINTS显示文摘当一套点的坐标被知道时, pairwise 在点之中的欧几里德几何学的距离能容易被计算。相反地,如果欧几里德几何学的距离矩阵被给,为那些点的一套坐标能被计算通过众所周知古典多维的可伸缩(MDS ) 。在这份报纸,我们考虑一些距离远离是精确的盒子(包含的大噪音或平错过) 。处于如此的一种状况,已知的距离的顺序(即,一些距离比其它大) 比就使用已知的距离的大小是经常产出点的更加精确的建设的珍贵信息。使用订购信息的方法一起作为 nonmetric MDS 被知道。在所有存在 nonmetric MDS 方法之中的一个挑战性的计算问题是经常有很多顺序的限制。在这份报纸,我们与顺序的限制作为一个矩阵优化问题扔了这个问题。我们然后改编一存在弄平牛顿方法到我们的矩阵问题。广泛的数字结果表明算法的效率,它能潜在地处理顺序的限制的一个很大的数字。 | Qingna Li Houduo Qi | 2017 | Journal of Computational Mathematics2017，35，4： | 0 |
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