Results 31 to 40 of about 510 (73)
Journal of Inequalities and ApplicationsIn this research, we introduce a novel optimization algorithm termed the dual-relaxed inertial alternating direction method of multipliers (DR-IADM), tailored for handling nonconvex and nonsmooth problems. These problems are characterized by an objective
Yang Liu, Long Wang, Yazheng Dang
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The Extended Second APG Method for Constrained DC Problems
AxiomsIn this paper, we develop the extended proximal gradient algorithm with Nesterov’s second acceleration (EAPGs) for constrained difference-of-convex (DC) optimization problems.
Ziye Liu, Huitao Ke, Chunguang Liu
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Journal of Inequalities and ApplicationsThe alternating direction method of multipliers (ADMM) has been widely used to solve linear constrained problems in signal processing, matrix decomposition, machine learning, and many other fields.
Zhonghui Xue +3 more
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A Simple and Efficient Algorithm for Nonlinear Model Predictive Control
, 2017 We present PANOC, a new algorithm for solving optimal control problems arising in nonlinear model predictive control (NMPC). A usual approach to this type of problems is sequential quadratic programming (SQP), which requires the solution of a quadratic ...
Patrinos, Panagiotis +3 more
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Convolutional Dictionary Learning: Acceleration and Convergence
, 2017 Convolutional dictionary learning (CDL or sparsifying CDL) has many applications in image processing and computer vision. There has been growing interest in developing efficient algorithms for CDL, mostly relying on the augmented Lagrangian (AL) method ...
Chun, Il Yong, Fessler, Jeffrey A.
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A Multi-step Inertial Forward--Backward Splitting Method for Non-convex Optimization
, 2016 In this paper, we propose a multi-step inertial Forward--Backward splitting algorithm for minimizing the sum of two non-necessarily convex functions, one of which is proper lower semi-continuous while the other is differentiable with a Lipschitz ...
Fadili, Jalal +2 more
core
Convergence of the Forward-Backward Algorithm: Beyond the Worst Case with the Help of Geometry
, 2017 We provide a comprehensive study of the convergence of forward-backward algorithm under suitable geometric conditions leading to fast rates. We present several new results and collect in a unified view a variety of results scattered in the literature ...
Garrigos, Guillaume +2 more
core
Optimization of a Fast Transform Structured as a Convolutional Tree [PDF]
, 2016 To reduce the dimension of large datasets, it is common to express each vector of this dataset using few atoms of a redundant dictionary. In order to select these atoms, many models and algorithms have been proposed, leading to state-of-the-art ...
Chabiron, Olivier +3 more
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Arcwise Analytic Stratification, Whitney Fibering Conjecture and Zariski Equisingularity
, 2017 In this paper we show Whitney's fibering conjecture in the real and complex, local analytic and global algebraic cases. For a given germ of complex or real analytic set, we show the existence of a stratification satisfying a strong (real arc-analytic ...
Parusiński, Adam, Paunescu, Laurentiu
core
Proximal Alternating Direction Network: A Globally Converged Deep Unrolling Framework
, 2017 Deep learning models have gained great success in many real-world applications. However, most existing networks are typically designed in heuristic manners, thus lack of rigorous mathematical principles and derivations.
Cheng, Shichao +4 more
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