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Deep Domain Decomposition Methods: Helmholtz Equation 期刊论文
ADVANCES IN APPLIED MATHEMATICS AND MECHANICS, 2023, 卷号: 15, 期号: 1, 页码: 118-138
Authors:  Li, Wuyang;  Wang, Ziming;  Cui, Tao;  Xu, Yingxiang;  Xiang, Xueshuang
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Helmholtz equation  deep learning  domain decomposition method  plane wave method  
Positivity and stability of timescale-type linear singular systems with time delays 期刊论文
SCIENCE CHINA-INFORMATION SCIENCES, 2022, 卷号: 65, 期号: 12, 页码: 16
Authors:  Lu, Xiaodong;  Li, Haitao;  Zhang, Xianfu
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positivity  stability  time delay  linear singular systems  timescale-type systems  
Distributed stochastic gradient tracking methods with momentum acceleration for non-convex optimization 期刊论文
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 2022, 页码: 42
Authors:  Gao, Juan;  Liu, Xin-Wei;  Dai, Yu-Hong;  Huang, Yakui;  Gu, Junhua
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Distributed non-convex optimization  Machine learning  Momentum methods  Optimization algorithms  Convergence rate  
Convergence of adaptive nonconforming finite element method for Stokes optimal control problems 期刊论文
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2022, 卷号: 412, 页码: 23
Authors:  Shen, Yue;  Gong, Wei;  Yan, Ningning
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Optimal control problem  Stokes equations  Control constraints  Adaptive nonconforming finite element method  Convergence and quasi-optimality  
Understanding the acceleration phenomenon via high-resolution differential equations 期刊论文
MATHEMATICAL PROGRAMMING, 2022, 卷号: 195, 期号: 1-2, 页码: 79-148
Authors:  Shi, Bin;  Du, Simon S.;  Jordan, Michael, I;  Su, Weijie J.
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Convex optimization  First-order method  Polyak's heavy ball method  Nesterov's accelerated gradient methods  Ordinary differential equation  Lyapunov function  Gradient minimization  
Differentially private distributed algorithms for stochastic aggregative games 期刊论文
AUTOMATICA, 2022, 卷号: 142, 页码: 13
Authors:  Wang, Jimin;  Zhang, Ji-Feng;  He, Xingkang
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Differential privacy  Stochastic aggregative games  Distributed algorithms  Stochastic approximation  
Linear convergence of an alternating polar decomposition method for low rank orthogonal tensor approximations 期刊论文
MATHEMATICAL PROGRAMMING, 2022, 页码: 60
Authors:  Hu, Shenglong;  Ye, Ke
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Orthogonally decomposable tensors  Low rank orthogonal tensor approximation  R-linear convergence  Sublinear convergence  Global convergence  
An adaptive group LASSO approach for domain selection in functional generalized linear models 期刊论文
JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2022, 卷号: 219, 页码: 13-32
Authors:  Sun, Yifan;  Wang, Qihua
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Functional data  Adaptive LASSO  Group LASSO  Null region detection  B-spline  
The augmented lagrangian method can approximately solve convex optimization with least constraint violation 期刊论文
MATHEMATICAL PROGRAMMING, 2022, 页码: 35
Authors:  Dai, Yu-Hong;  Zhang, Liwei
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Convex optimization  Least constraint violation  Augmented Lagrangian method  Shifted problem  Optimal value mapping  Solution mapping  Dual function  Conjugate dual  
Two-sample functional linear models with functional responses 期刊论文
JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2022, 卷号: 218, 页码: 85-105
Authors:  Xu, Wenchao;  Lin, Hongmei;  Zhang, Riquan;  Liang, Hua
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Asymptotic normality  Functional linear regression  Functional response  Functional principal component analysis  Rate of convergence  Semiparametric comparison