Search Results - Difference of convex functions algorithm

Impulse Noise Image Restoration Using Nonconvex Variational Model and Difference of Convex Functions Algorithm by Zhang, Benxin, Zhu, Guopu, Zhu, Zhibin, Zhang, Hongli, Zhou, Yicong, Kwong, Sam

“…> norm data fitting term and a total variation (TV) regularization. However, a convex optimization method designed in this way always yields staircase artifacts…”
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Universum parametric-margin ν-support vector machine for classification using the difference of convex functions algorithm by Moosaei, Hossein, Bazikar, Fatemeh, Ketabchi, Saeed, Hladík, Milan

“… -SVM, which is a nonconvex optimization problem, is transformed into an unconstrained optimization problem so that the objective function can be treated as a difference of two convex functions (DC…”
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A Difference of Convex Functions Algorithm for Switched Linear Regression by Tao Pham Dinh, Hoai Minh Le, Hoai An Le Thi, Lauer, Fabien

“… minimized. The technical note proposes a new approach to the optimization of this nonsmooth and nonconvex objective function, which relies on Difference of Convex (DC…”
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Long-Short Portfolio Optimization Under Cardinality Constraints by Difference of Convex Functions Algorithm by Le Thi, Hoai An, Moeini, Mahdi

“… Attempting to use DC (Difference of Convex functions) programming and DCA (DC Algorithms), an efficient approach in non-convex programming framework…”
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A unified equivalent model of the l0 minimization model for structural damage identification by Song, Xueli, Ma, Xiao, Li, Rongpeng, Yi, Wen, Ma, Lingjuan, Zheng, Supei, Wang, Kaiming

“… Many existing approximation models have approximately solved the original model because it is NP-hard, by replacing the l0-norm with continuous sparsity-promoting functions, which inevitably reduces…”
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The Boosted DC Algorithm for Linearly Constrained DC Programming by Aragón-Artacho, F. J., Campoy, R., Vuong, P. T.

“…The Boosted Difference of Convex functions Algorithm (BDCA) has been recently introduced to accelerate the performance of the classical Difference of Convex functions Algorithm (DCA…”
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Sparse-View Spectral CT Reconstruction Using Spectral Patch-Based Low-Rank Penalty by Kyungsang Kim, Jong Chul Ye, Worstell, William, Jinsong Ouyang, Rakvongthai, Yothin, El Fakhri, Georges, Quanzheng Li

“…Spectral computed tomography (CT) is a promising technique with the potential for improving lesion detection, tissue characterization, and material…”
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Minimization of transformed L1 penalty: theory, difference of convex function algorithm, and robust application in compressed sensing by Zhang, Shuai, Xin, Jack

“…We study the minimization problem of a non-convex sparsity promoting penalty function, the transformed l 1 (TL1…”
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On solving difference of convex functions programs with linear complementarity constraints by Le Thi, Hoai An, Nguyen, Thi Minh Tam, Dinh, Tao Pham

“… The difference of convex functions algorithm (DCA), an efficient approach in nonconvex programming framework, is then developed to solve the resulting problems…”
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A boosted DC algorithm for non-differentiable DC components with non-monotone line search by Ferreira, O. P., Santos, E. M., Souza, J. C. O.

“…We introduce a new approach to apply the boosted difference of convex functions algorithm (BDCA…”
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Optimization of Device-Free Localization with Springback Dual Models: A Synthetic and Analytical Framework by Li, Jinan, Tan, Benying, Qin, Yang, Mo, Yaoyao

“… of getting stuck in local optima. To address these issues, this study proposes a synthetic model based on a novel weakly convex penalty function called Springback…”
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A Preconditioned Difference of Convex Algorithm for Truncated Quadratic Regularization with Application to Imaging by Deng, Shengxiang, Sun, Hongpeng

“… We cooperated the classical preconditioned iterations for linear equations into the nonlinear difference of convex functions algorithms with extrapolation…”
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A new device-free localization method for RSS data with considering correlations by Xia, Ziwei, Tan, Benying, Zhao, Haoli, Ding, Shuxue, Li, Yujie

“…Device-free localization (DFL) is an emerging intelligent sensing technique with challenging issues due to the highly correlated data. Localization performance…”
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Feature selection in machine learning: an exact penalty approach using a Difference of Convex function Algorithm by Le Thi, Hoai An, Le, Hoai Minh, Pham Dinh, Tao

“… 0 -regularization problem. Using a new result on exact penalty techniques we reformulate equivalently the original problem as a Difference of Convex (DC) functions program…”
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Unknown-but-bounded uncertainty propagation in spacecraft structural system: Interval reduced basis method and its integrated framework by Lyu, Zheng, Yang, Yaowen, Xia, Haijun

“…Uncertainty propagation analysis is a key issue for the safety and optimal design of spacecraft structures. This paper proposes an interval reduced basis…”
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Feature selection for linear SVMs under uncertain data: Robust optimization based on difference of convex functions algorithms by Le Thi, Hoai An, Vo, Xuan Thanh, Pham Dinh, Tao

“… The difficulty in treating ℓ0-norm in feature selection problem is overcome by using appropriate approximations and Difference of Convex functions (DC…”
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Using Positive Spanning Sets to Achieve d-Stationarity with the Boosted DC Algorithm by Artacho, F. J. Aragón, Campoy, R., Vuong, P. T.

“…The Difference of Convex functions Algorithm (DCA) is widely used for minimizing the difference of two convex functions…”
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Learning sparse classifiers with difference of convex functions algorithms by Ong, Cheng Soon, An, Le Thi Hoai

“… ℓ 1 regularization with hinge loss, and the ramp loss versions of approximate ℓ 0 and capped ℓ 1 regularization. We derive difference of convex functions algorithms…”
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Smoothing techniques and difference of convex functions algorithms for image reconstructions by Mau Nam, Nguyen, Hoai An, Le Thi, Giles, Daniel, Thai An, Nguyen

“… As an application, we provide a simple approach to image reconstructions based on Nesterov's smoothing and algorithms for minimizing differences of convex (DC…”
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The Boosted Difference of Convex Functions Algorithm for Value-at-Risk Constrained Portfolio Optimization by Thormann, Marah-Lisanne, Phan Tu Vuong, Zemkoho, Alain B

“…) functions representation of the VaR can be derived. Wozabal (2012) showed that this yields a solution to a VaR constrained Markowitz style portfolio selection problem using the Difference of Convex Functions Algorithm (DCA…”
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