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检索条件"主题词=weakly convex function"
7 条 记 录,以下是1-10 订阅
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Linearly-Involved Moreau-Enhanced-Over-Subspace Model: Debiased Sparse Modeling and Stable Outlier-Robust Regression
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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2023年 71卷 1232-1247页
作者: Yukawa, Masahiro Kaneko, Hiroyuki Suzuki, Kyohei Yamada, Isao Keio Univ Dept Elect & Elect Engn Yokohama Kanagawa 2238522 Japan Tokyo Inst Technol Dept Informat & Commun Engn Meguro Ku Tokyo 1528550 Japan
We present an efficient mathematical framework to derive promising methods that enjoy "enhanced" desirable properties. The popular minimax concave penalty for sparse modeling subtracts, from the l(1) norm, i... 详细信息
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An Adaptive Alternating Direction Method of Multipliers
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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2022年 第3期195卷 1019-1055页
作者: Bartz, Sedi Campoy, Ruben Phan, Hung M. Univ Massachusetts Lowell Kennedy Coll Sci Dept Math Sci Lowell MA USA Univ Valencia Dept Stat & Operat Res Valencia Spain
The alternating direction method of multipliers (ADMM) is a powerful splitting algorithm for linearly constrained convex optimization problems. In view of its popularity and applicability, a growing attention is drawn... 详细信息
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A fundamental proof of convergence of alternating direction method of multipliers for weakly convex optimization
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JOURNAL OF INEQUALITIES AND APPLICATIONS 2019年 第1期2019卷 1-21页
作者: Zhang, Tao Shen, Zhengwei Univ Sci & Technol Beijing Sch Math & Phys Beijing Peoples R China
The convergence of the alternating direction method of multipliers (ADMMs) algorithm to convex/nonconvex combinational optimization has been well established in the literature. Due to the extensive applications of a w... 详细信息
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Growth Conditions on a function and the Error Bound Condition
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MATHEMATICAL NOTES 2021年 第3-4期109卷 638-643页
作者: Balashov, M. V. Russian Acad Sci Trapeznikov Inst Control Sci Moscow 117997 Russia
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Stable Robust Regression under Sparse Outlier and Gaussian Noise  30
Stable Robust Regression under Sparse Outlier and Gaussian N...
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30th European Signal Processing Conference (EUSIPCO)
作者: Yukawa, Masahiro Suzuki, Kyohei Yamada, Isao Keio Univ Dept Elect & Elect Engn Tokyo Japan Tokyo Inst Technol Dept Informat & Commun Engn Tokyo Japan
We propose an efficient regression method which is highly robust against outliers and stable even in the severely noisy situations. The robustness here comes from the adoption of the minimax concave loss, while the st... 详细信息
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EXTERNAL DIVISION OF TWO PROXIMITY OPERATORS: AN APPLICATION TO SIGNAL RECOVERY WITH STRUCTURED SPARSITY  49
EXTERNAL DIVISION OF TWO PROXIMITY OPERATORS: AN APPLICATION...
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49th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Suzuki, Kyohei Yukawa, Masahiro Keio Univ Dept Elect & Elect Engn Minato City Tokyo Japan
This paper studies the external division operator, an external division (an affine combination with positive and negative weights) of two proximity operators. We show that the external division operator is cocoercive ... 详细信息
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A VARIABLE SMOOTHING FOR NONconvexLY CONSTRAINED NONSMOOTH OPTIMIZATION WITH APPLICATION TO SPARSE SPECTRAL CLUSTERING  49
A VARIABLE SMOOTHING FOR NONCONVEXLY CONSTRAINED NONSMOOTH O...
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49th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Kume, Keita Yamada, Isao Tokyo Inst Technol Dept Informat & Commun Engn Tokyo Japan
We propose a variable smoothing algorithm for solving nonconvexly constrained nonsmooth optimization problems. The target problem has two issues that need to be addressed: (i) the nonconvex constraint and (ii) the non... 详细信息
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