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我们研究Stiefel流形上线性规划(LPS):其目标是线性函数,变量是p个n维空间正交向量(即Stiefel流形约束,p<=n),额外再满足k个线性约束。据我们所知,该模型首次被研究。k=0的(LPS)是一个经典的多项式可解问题。
In this work, synthesis of robust memory modes for linear quantum passive systems in the presence of unknown inputs has been studied, aimed at facilitating secure storage and communication of quantum ...
In this talk, we discuss the approximation and computation for the linear and nonlinear eigenvalue problems in photonic crystals. We discretize the shifted Maxwell operator with edge finite elements a...
We develop and compare two algorithms for computing first-order right-hand factors in the ring of linear Mahler operators l_r M^r+?+l_1 M+l_0 where l_0,…,l_r are polynomials in x and Mx=x^b M for some...
In this talk, we introduce a modified classical algorithm to solve linear systems in a model that resembles the QRAM used by quantum linear solvers. Specifically, we demonstrate that for the linear sy...
Nonconvex minimax problems have attracted wide attention in machine learning, signal processing and many other fields in recent years. In this paper, we propose a primal dual alternating proximal grad...
Several topological optimization problems involving surfaces can be turned into linear programming problems. In the case of stable commutator length, this was first discovered by Danny Calegari in the...
In this talk, we consider a distributed interval optimization problem (DIOP) with uncertainties, whose global function is formed by local convex interval functions. In seeking Pareto solutions for dis...
In this talk, we present numerical approximations of a phase-field model for two-phase ferrofluids, which consists of the Navier-Stokes equations, the Cahn-Hilliard equation, the magnetostatic equatio...
This paper proposes a method to accelerate calculation for generalized linear models in big data. We separate the covariates of full model into several groups to build candidate models. In the process...
Hypothesis testing on high-dimensional fixed effects is indispensable for investigating the utility of the predictors on response. In this case, the conventional frequentist methods designed for cases...
Linear mixed model is a popular and common modeling method in statistical analysis. It is computationally difficult to obtain parameter estimates in linear mixed model for big data. The current subsam...
近日,数学学院2019级硕士研究生舒希超收到了来自理论计算机领域顶级会议SODA(ACM-SIAM Symposium of Discrete Algorithms)的论文录用信。舒希超与美国罗德岛大学的韩杰研究员和山大数学学院的王光辉教授合作的论文《Non-linear Hamilton cycles in linear quasi-random hypergraphs》将发表在2021年1月的...
鲁东大学运筹学课件 Lecture-Linear Programming。

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