Search Results - Boosted difference of convex functions algorithm

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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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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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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The Boosted Difference of Convex Functions Algorithm for Value-at-Risk Constrained Portfolio Optimization by Thormann, Marah-Lisanne, Phan Tu Vuong, Zemkoho, Alain B

“…). A recent algorithmic extension is the so-called Boosted Difference of Convex Functions Algorithm (BDCA…”
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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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An Inexact Boosted Difference of Convex Algorithm for Nondifferentiable Functions by Ferreira, Orizon P, Mordukhovich, Boris S, Santos, Wilkreffy M S, Souza, João Carlos O

“…In this paper, we introduce an inexact approach to the Boosted Difference of Convex Functions Algorithm (BDCA…”
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The Boosted DC Algorithm for linearly constrained DC programming by Aragón Artacho, Francisco J, Campoy, Rubén, Vuong, Phan 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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The Boosted DC Algorithm for nonsmooth functions by Aragón Artacho, Francisco J, Vuong, Phan T

“…The Boosted Difference of Convex functions Algorithm (BDCA) was recently proposed for minimizing smooth difference of convex (DC) functions…”
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A boosted DC algorithm for non-differentiable DC components with non-monotone line search by Ferreira, Orizon P, Santos, Elianderson M, Souza, João Carlos O

“…We introduce a new approach to apply the boosted difference of convex functions algorithm (BDCA…”
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The Boosted DC Algorithm for Clustering with Constraints by Tran, Tuyen, Figenschou, Kate, Phan Tu Vuong

“…This paper aims to investigate the effectiveness of the recently proposed Boosted Difference of Convex functions Algorithm (BDCA…”
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Qualitative Analysis and Adaptive Boosted DCA for Generalized Multi-Source Weber Problems by Vo Si Trong Long, Nguyen Mau Nam, Tran, Tuyen, Nguyen Thi Thu Van

“… Second, we apply Nesterov's smoothing and the adaptive Boosted Difference of Convex functions Algorithm (BDCA…”
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The Boosted Double-proximal Subgradient Algorithm for nonconvex optimization by Aragón-Artacho, Francisco J., Pérez-Aros, Pedro, Torregrosa-Belén, David

“…In this paper we introduce the Boosted Double-proximal Subgradient Algorithm (BDSA), a novel splitting algorithm designed to address general structured…”
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Image denoising with a non-monotone boosted DCA for non-convex models by Ferreira, O.P., Rabelo, R.A.L., Ribeiro, P.H.A., Santos, E.M., Souza, J.C.O.

“…), an accelerated variant of the Difference of Convex Algorithm (DCA), with a non-convex version of the total variation (TV…”
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A New Boosted Proximal Point Algorithm for Minimizing Nonsmooth DC Functions by Alizadeh Tabrizian, Amir Hamzeh, Bidabadi, Narges

“… and global optimization. In this article, we introduce new algorithm to minimize the difference of a continuously differentiable function and a convex function that accelerate the convergence of the classical proximal point algorithm…”
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Using positive spanning sets to achieve d-stationarity with the Boosted DC Algorithm by Aragón Artacho, Francisco J, Campoy, Rubén, Vuong, Phan T

“…The Difference of Convex functions Algorithm (DCA) is widely used for minimizing the difference of two convex functions…”
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A non-monotone proximal point method for image reconstruction using non-convex total variation models by Rabelo, R.A.L., Ribeiro, P.H.A., Santos, W.M.S., Silva, R.C.C., Souza, J.C.O.

“…) when applied to image denoising and filtering tasks. In this work, we propose a boosted version of the PPM for image denoising, called nmPPMDC, using a non-convex Total Variation model…”
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A Boosted-DCA with Power-Sum-DC Decomposition for Linearly Constrained Polynomial Programs by Zhang, Hu, Niu, Yi-Shuai

“…This paper proposes a novel Difference-of-Convex (DC) decomposition for polynomials using a power-sum representation, achieved by solving a sparse linear system…”
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Boosted scaled subgradient method for DC programming by Ferreira, Orizon P, Santos, Elianderson M, Souza, João Carlos O

“…) to minimize the difference of two convex functions (DC functions), where the first function is differentiable and the second one is possibly non-smooth…”
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High-order Moment Portfolio Optimization via An Accelerated Difference-of-Convex Programming Approach and Sums-of-Squares by Yi-Shuai Niu, Ya-Juan, Wang, Hoai An Le Thi, Dinh Tao Pham

“…The Mean-Variance-Skewness-Kurtosis (MVSK) portfolio optimization model is a quartic nonconvex polynomial minimization problem over a polytope, which can be formulated as a Difference-of-Convex (DC) program…”
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Boosted Lasso

“… (L1 penalized convex loss). It consists of both a forward step and a backward step and uses differences of functions instead of gradient…”
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