Výsledky vyhľadávania - Boosted difference of convex functions algorithm

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  1. 1

    The Boosted DC Algorithm for Linearly Constrained DC Programming Autor Aragón-Artacho, F. J., Campoy, R., Vuong, P. T.

    ISSN: 1877-0533, 1877-0541
    Vydavateľské údaje: Dordrecht Springer Netherlands 01.12.2022
    Vydané v Set-valued and variational analysis (01.12.2022)
    “…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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    Journal Article
  2. 2

    A boosted DC algorithm for non-differentiable DC components with non-monotone line search Autor Ferreira, O. P., Santos, E. M., Souza, J. C. O.

    ISSN: 0926-6003, 1573-2894
    Vydavateľské údaje: New York Springer US 01.07.2024
    “…We introduce a new approach to apply the boosted difference of convex functions algorithm (BDCA…”
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    Journal Article
  3. 3

    Using Positive Spanning Sets to Achieve d-Stationarity with the Boosted DC Algorithm Autor Artacho, F. J. Aragón, Campoy, R., Vuong, P. T.

    ISSN: 2305-221X, 2305-2228, 2305-2228
    Vydavateľské údaje: Singapore Springer Nature Singapore 01.06.2020
    Vydané v Vietnam journal of mathematics (01.06.2020)
    “…The Difference of Convex functions Algorithm (DCA) is widely used for minimizing the difference of two convex functions…”
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    Journal Article
  4. 4

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

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 14.02.2024
    Vydané v arXiv.org (14.02.2024)
    “…). A recent algorithmic extension is the so-called Boosted Difference of Convex Functions Algorithm (BDCA…”
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    Paper
  5. 5

    Universum parametric-margin ν-support vector machine for classification using the difference of convex functions algorithm Autor Moosaei, Hossein, Bazikar, Fatemeh, Ketabchi, Saeed, Hladík, Milan

    ISSN: 0924-669X, 1573-7497
    Vydavateľské údaje: New York Springer US 01.02.2022
    “… -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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    Journal Article
  6. 6

    An Inexact Boosted Difference of Convex Algorithm for Nondifferentiable Functions Autor Ferreira, Orizon P, Mordukhovich, Boris S, Santos, Wilkreffy M S, Souza, João Carlos O

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 07.12.2024
    Vydané v arXiv.org (07.12.2024)
    “…In this paper, we introduce an inexact approach to the Boosted Difference of Convex Functions Algorithm (BDCA…”
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  7. 7

    The Boosted DC Algorithm for linearly constrained DC programming Autor Aragón Artacho, Francisco J, Campoy, Rubén, Vuong, Phan T

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 02.08.2022
    Vydané v arXiv.org (02.08.2022)
    “…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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    Paper
  8. 8

    The Boosted DC Algorithm for nonsmooth functions Autor Aragón Artacho, Francisco J, Vuong, Phan T

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 23.07.2019
    Vydané v arXiv.org (23.07.2019)
    “…The Boosted Difference of Convex functions Algorithm (BDCA) was recently proposed for minimizing smooth difference of convex (DC) functions…”
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    Paper
  9. 9

    A boosted DC algorithm for non-differentiable DC components with non-monotone line search Autor Ferreira, Orizon P, Santos, Elianderson M, Souza, João Carlos O

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 17.06.2022
    Vydané v arXiv.org (17.06.2022)
    “…We introduce a new approach to apply the boosted difference of convex functions algorithm (BDCA…”
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    Paper
  10. 10

    The Boosted DC Algorithm for Clustering with Constraints Autor Tran, Tuyen, Figenschou, Kate, Phan Tu Vuong

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 22.10.2023
    Vydané v arXiv.org (22.10.2023)
    “…This paper aims to investigate the effectiveness of the recently proposed Boosted Difference of Convex functions Algorithm (BDCA…”
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    Paper
  11. 11

    Qualitative Analysis and Adaptive Boosted DCA for Generalized Multi-Source Weber Problems Autor Vo Si Trong Long, Nguyen Mau Nam, Tran, Tuyen, Nguyen Thi Thu Van

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 20.09.2024
    Vydané v arXiv.org (20.09.2024)
    “… Second, we apply Nesterov's smoothing and the adaptive Boosted Difference of Convex functions Algorithm (BDCA…”
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    Paper
  12. 12

    The Boosted Double-proximal Subgradient Algorithm for nonconvex optimization Autor Aragón-Artacho, Francisco J., Pérez-Aros, Pedro, Torregrosa-Belén, David

    ISSN: 0025-5610, 1436-4646
    Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2025
    Vydané v Mathematical programming (01.11.2025)
    “…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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    Journal Article
  13. 13

    Image denoising with a non-monotone boosted DCA for non-convex models Autor Ferreira, O.P., Rabelo, R.A.L., Ribeiro, P.H.A., Santos, E.M., Souza, J.C.O.

    ISSN: 0045-7906, 1879-0755
    Vydavateľské údaje: Elsevier Ltd 01.07.2024
    Vydané v Computers & electrical engineering (01.07.2024)
    “…), an accelerated variant of the Difference of Convex Algorithm (DCA), with a non-convex version of the total variation (TV…”
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    Journal Article
  14. 14

    A New Boosted Proximal Point Algorithm for Minimizing Nonsmooth DC Functions Autor Alizadeh Tabrizian, Amir Hamzeh, Bidabadi, Narges

    ISSN: 0163-0563, 1532-2467
    Vydavateľské údaje: Abingdon Taylor & Francis 26.08.2022
    “… 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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    Journal Article
  15. 15

    Using positive spanning sets to achieve d-stationarity with the Boosted DC Algorithm Autor Aragón Artacho, Francisco J, Campoy, Rubén, Vuong, Phan T

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 12.02.2020
    Vydané v arXiv.org (12.02.2020)
    “…The Difference of Convex functions Algorithm (DCA) is widely used for minimizing the difference of two convex functions…”
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    Paper
  16. 16

    A non-monotone proximal point method for image reconstruction using non-convex total variation models Autor Rabelo, R.A.L., Ribeiro, P.H.A., Santos, W.M.S., Silva, R.C.C., Souza, J.C.O.

    ISSN: 0045-7906
    Vydavateľské údaje: Elsevier Ltd 01.08.2025
    Vydané v Computers & electrical engineering (01.08.2025)
    “…) 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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    Journal Article
  17. 17

    A Boosted-DCA with Power-Sum-DC Decomposition for Linearly Constrained Polynomial Programs Autor Zhang, Hu, Niu, Yi-Shuai

    ISSN: 0022-3239, 1573-2878
    Vydavateľské údaje: New York Springer US 01.05.2024
    “…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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    Journal Article
  18. 18

    Boosted scaled subgradient method for DC programming Autor Ferreira, Orizon P, Santos, Elianderson M, Souza, João Carlos O

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 19.03.2021
    Vydané v arXiv.org (19.03.2021)
    “…) 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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  19. 19

    High-order Moment Portfolio Optimization via An Accelerated Difference-of-Convex Programming Approach and Sums-of-Squares Autor Yi-Shuai Niu, Ya-Juan, Wang, Hoai An Le Thi, Dinh Tao Pham

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 06.05.2022
    Vydané v arXiv.org (06.05.2022)
    “…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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    Paper
  20. 20

    Boosted Lasso

    Vydavateľské údaje: Hampton NASA/Langley Research Center 01.12.2004
    “… (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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    Technical Report