François Glineur
(Francois Glineur)

Personal Details

First Name:	Francois
Middle Name:
Last Name:	Glineur
Suffix:
RePEc Short-ID:	pgl27
	[This author has chosen not to make the email address public]
Terminal Degree:	2001 (from RePEc Genealogy)

Affiliation

Center for Operations Research and Econometrics (CORE)
Louvain Institute of Data Analysis and Modelling in Economics and Statistics (LIDAM)
Université Catholique de Louvain

Louvain-la-Neuve, Belgium
http://www.uclouvain.be/en-core.html
RePEc:edi:coreebe (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. De Klerk, Etienne & Glineur, François & Taylor, Adrien B., 2020. "Worst-Case Convergence Analysis of Inexact Gradient and Newton Methods Through Semidefinite Programming Performance Estimation," LIDAM Reprints CORE 3134, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   • de Klerk, Etienne & Glineur, Francois & Taylor, Adrien, 2020. "Worst-case convergence analysis of inexact gradient and Newton methods through semidefinite programming performance estimation," Other publications TiSEM 03a65c83-e88f-4723-a50e-2, Tilburg University, School of Economics and Management.

   Cited by:

   1. André Uschmajew & Bart Vandereycken, 2022. "A Note on the Optimal Convergence Rate of Descent Methods with Fixed Step Sizes for Smooth Strongly Convex Functions," Journal of Optimization Theory and Applications, Springer, vol. 194(1), pages 364-373, July.
   2. Abbaszadehpeivasti, Hadi & de Klerk, Etienne & Zamani, Moslem, 2023. "Convergence rate analysis of randomized and cyclic coordinate descent for convex optimization through semidefinite programming," Other publications TiSEM 88512ac0-c26a-4a99-b840-3, Tilburg University, School of Economics and Management.
   3. Abbaszadehpeivasti, Hadi & de Klerk, Etienne & Zamani, Moslem, 2022. "The exact worst-case convergence rate of the gradient method with fixed step lengths for L-smooth functions," Other publications TiSEM 061688c6-f97c-4024-bb5b-1, Tilburg University, School of Economics and Management.
   4. Roland Hildebrand, 2021. "Optimal step length for the Newton method: case of self-concordant functions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 94(2), pages 253-279, October.

2. Ion Necoara & Yurii Nesterov & François Glineur, 2019. "Linear convergence of first order methods for non-strongly convex optimization," LIDAM Reprints CORE 3000, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

   Cited by:

   1. Vassilis Apidopoulos & Nicolò Ginatta & Silvia Villa, 2022. "Convergence rates for the heavy-ball continuous dynamics for non-convex optimization, under Polyak–Łojasiewicz condition," Journal of Global Optimization, Springer, vol. 84(3), pages 563-589, November.
   2. Ion Necoara, 2021. "General Convergence Analysis of Stochastic First-Order Methods for Composite Optimization," Journal of Optimization Theory and Applications, Springer, vol. 189(1), pages 66-95, April.
   3. Ching-pei Lee & Stephen J. Wright, 2019. "Inexact Successive quadratic approximation for regularized optimization," Computational Optimization and Applications, Springer, vol. 72(3), pages 641-674, April.
   4. Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact Worst-Case Convergence Rates of the Proximal Gradient Method for Composite Convex Minimization," Journal of Optimization Theory and Applications, Springer, vol. 178(2), pages 455-476, August.
      • Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact worst-case convergence rates of the proximal gradient method for composite convex minimization," LIDAM Reprints CORE 2975, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   5. Huynh Ngai & Ta Anh Son, 2022. "Generalized Nesterov’s accelerated proximal gradient algorithms with convergence rate of order o(1/k2)," Computational Optimization and Applications, Springer, vol. 83(2), pages 615-649, November.
   6. Yunier Bello-Cruz & Guoyin Li & Tran Thai An Nghia, 2022. "Quadratic Growth Conditions and Uniqueness of Optimal Solution to Lasso," Journal of Optimization Theory and Applications, Springer, vol. 194(1), pages 167-190, July.
   7. Yunier Bello-Cruz & Guoyin Li & Tran T. A. Nghia, 2021. "On the Linear Convergence of Forward–Backward Splitting Method: Part I—Convergence Analysis," Journal of Optimization Theory and Applications, Springer, vol. 188(2), pages 378-401, February.
   8. Woocheol Choi & Doheon Kim & Seok-Bae Yun, 2022. "Convergence Results of a Nested Decentralized Gradient Method for Non-strongly Convex Problems," Journal of Optimization Theory and Applications, Springer, vol. 195(1), pages 172-204, October.
   9. Benjamin Grimmer, 2023. "General Hölder Smooth Convergence Rates Follow from Specialized Rates Assuming Growth Bounds," Journal of Optimization Theory and Applications, Springer, vol. 197(1), pages 51-70, April.
   10. Olivier Fercoq & Zheng Qu, 2020. "Restarting the accelerated coordinate descent method with a rough strong convexity estimate," Computational Optimization and Applications, Springer, vol. 75(1), pages 63-91, January.
   11. Zamani, Moslem & Abbaszadehpeivasti, Hadi & de Klerk, Etienne, 2023. "The exact worst-case convergence rate of the alternating direction method of multipliers," Other publications TiSEM f30ae9e6-ed19-423f-bd1e-0, Tilburg University, School of Economics and Management.
   12. Xiaoya Zhang & Wei Peng & Hui Zhang, 2022. "Inertial proximal incremental aggregated gradient method with linear convergence guarantees," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 96(2), pages 187-213, October.
   13. Wei Peng & Hui Zhang & Xiaoya Zhang & Lizhi Cheng, 2020. "Global complexity analysis of inexact successive quadratic approximation methods for regularized optimization under mild assumptions," Journal of Global Optimization, Springer, vol. 78(1), pages 69-89, September.

3. Ion Necoara & Andrei Patrascu & François Glineur, 2019. "Complexity of first-order inexact Lagrangian and penalty methods for conic convex programming," LIDAM Reprints CORE 3004, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

   Cited by:

   1. Qihang Lin & Runchao Ma & Yangyang Xu, 2022. "Complexity of an inexact proximal-point penalty method for constrained smooth non-convex optimization," Computational Optimization and Applications, Springer, vol. 82(1), pages 175-224, May.
   2. Tianxiao Sun & Ion Necoara & Quoc Tran-Dinh, 2020. "Composite convex optimization with global and local inexact oracles," Computational Optimization and Applications, Springer, vol. 76(1), pages 69-124, May.

4. Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact worst-case convergence rates of the proximal gradient method for composite convex minimization," LIDAM Reprints CORE 2975, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   • Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact Worst-Case Convergence Rates of the Proximal Gradient Method for Composite Convex Minimization," Journal of Optimization Theory and Applications, Springer, vol. 178(2), pages 455-476, August.

   Cited by:

   1. André Uschmajew & Bart Vandereycken, 2022. "A Note on the Optimal Convergence Rate of Descent Methods with Fixed Step Sizes for Smooth Strongly Convex Functions," Journal of Optimization Theory and Applications, Springer, vol. 194(1), pages 364-373, July.
   2. Donghwan Kim & Jeffrey A. Fessler, 2021. "Optimizing the Efficiency of First-Order Methods for Decreasing the Gradient of Smooth Convex Functions," Journal of Optimization Theory and Applications, Springer, vol. 188(1), pages 192-219, January.
   3. Sandra S. Y. Tan & Antonios Varvitsiotis & Vincent Y. F. Tan, 2021. "Analysis of Optimization Algorithms via Sum-of-Squares," Journal of Optimization Theory and Applications, Springer, vol. 190(1), pages 56-81, July.
   4. Wei Peng & Hui Zhang & Xiaoya Zhang & Lizhi Cheng, 2020. "Global complexity analysis of inexact successive quadratic approximation methods for regularized optimization under mild assumptions," Journal of Global Optimization, Springer, vol. 78(1), pages 69-89, September.

5. Clintin P. Davis-Stober & Jean-Paul Doignon & Samuel Fiorini & François Glineur & Michel Regenwetter, 2018. "Extended formulations for order polytopes through network flows," LIDAM Reprints CORE 2987, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

   Cited by:

   1. Jean-Paul Doignon & Kota Saito, 2022. "Adjacencies on random ordering polytopes and flow polytopes," Papers 2207.06925, arXiv.org.

6. Ion NECOARA & Yurii NESTEROV & François GLINEUR, 2017. "Random block coordinate descent methods for linearly constrained optimization over networks," LIDAM Reprints CORE 2844, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   • Ion Necoara & Yurii Nesterov & François Glineur, 2017. "Random Block Coordinate Descent Methods for Linearly Constrained Optimization over Networks," Journal of Optimization Theory and Applications, Springer, vol. 173(1), pages 227-254, April.

   Cited by:

   1. Qin Wang & Weiguo Li & Wendi Bao & Feiyu Zhang, 2022. "Accelerated Randomized Coordinate Descent for Solving Linear Systems," Mathematics, MDPI, vol. 10(22), pages 1-20, November.
   2. Andrea Cristofari, 2019. "An almost cyclic 2-coordinate descent method for singly linearly constrained problems," Computational Optimization and Applications, Springer, vol. 73(2), pages 411-452, June.
   3. Sjur Didrik Flåm, 2020. "Emergence of price-taking Behavior," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 70(3), pages 847-870, October.
   4. Sjur Didrik Flåm, 2019. "Blocks of coordinates, stochastic programming, and markets," Computational Management Science, Springer, vol. 16(1), pages 3-16, February.
   5. Jin Zhang & Xide Zhu, 2022. "Linear Convergence of Prox-SVRG Method for Separable Non-smooth Convex Optimization Problems under Bounded Metric Subregularity," Journal of Optimization Theory and Applications, Springer, vol. 192(2), pages 564-597, February.

7. Nicolas GILLIS & François GLINEUR & Arnaud VANDAELE, 2017. "On the linear extension complexity of regular n-gons," LIDAM Reprints CORE 2830, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

   Cited by:

   1. Arnaud Vandaele & François Glineur & Nicolas Gillis, 2018. "Algorithms for positive semidefinite factorization," Computational Optimization and Applications, Springer, vol. 71(1), pages 193-219, September.

8. TAYLOR, Adrien B. & HENDRICKX, Julien M. & François GLINEUR, 2016. "Exact worst-case performance of first-order methods for composite convex optimization," LIDAM Discussion Papers CORE 2016052, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   • Adrien B. TAYLOR & Julien M. HENDRICKX & François GLINEUR, 2017. "Exact worst-case performance of first-order methods for composite convex optimization," LIDAM Reprints CORE 2875, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

   Cited by:

   1. Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact Worst-Case Convergence Rates of the Proximal Gradient Method for Composite Convex Minimization," Journal of Optimization Theory and Applications, Springer, vol. 178(2), pages 455-476, August.
      • Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact worst-case convergence rates of the proximal gradient method for composite convex minimization," LIDAM Reprints CORE 2975, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   2. Abbaszadehpeivasti, Hadi & de Klerk, Etienne & Zamani, Moslem, 2022. "The exact worst-case convergence rate of the gradient method with fixed step lengths for L-smooth functions," Other publications TiSEM 061688c6-f97c-4024-bb5b-1, Tilburg University, School of Economics and Management.
   3. Roland Hildebrand, 2021. "Optimal step length for the Newton method: case of self-concordant functions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 94(2), pages 253-279, October.
   4. Sandra S. Y. Tan & Antonios Varvitsiotis & Vincent Y. F. Tan, 2021. "Analysis of Optimization Algorithms via Sum-of-Squares," Journal of Optimization Theory and Applications, Springer, vol. 190(1), pages 56-81, July.
   5. Donghwan Kim & Jeffrey A. Fessler, 2017. "On the Convergence Analysis of the Optimized Gradient Method," Journal of Optimization Theory and Applications, Springer, vol. 172(1), pages 187-205, January.

9. DE KLERK, Etienne & GLINEUR, François & TAYLOR, Adrien B., 2016. "On the Worst-case Complexity of the Gradient Method with Exact Line Search for Smooth Strongly Convex Functions," LIDAM Discussion Papers CORE 2016027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   • de Klerk, Etienne & Glineur, Francois & Taylor, Adrien, 2017. "On the worst-case complexity of the gradient method with exact line search for smooth strongly convex functions," Other publications TiSEM 8cc0e8dd-b6cd-4f4f-9dcb-9, Tilburg University, School of Economics and Management.
   • Etienne de Klerk & François Glineur & Adrien B. Taylor, 2017. "On the worst-case complexity of the gradient method with exact line search for smooth strongly convex functions," LIDAM Reprints CORE 2918, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

   Cited by:

   1. André Uschmajew & Bart Vandereycken, 2022. "A Note on the Optimal Convergence Rate of Descent Methods with Fixed Step Sizes for Smooth Strongly Convex Functions," Journal of Optimization Theory and Applications, Springer, vol. 194(1), pages 364-373, July.
   2. Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact Worst-Case Convergence Rates of the Proximal Gradient Method for Composite Convex Minimization," Journal of Optimization Theory and Applications, Springer, vol. 178(2), pages 455-476, August.
      • Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact worst-case convergence rates of the proximal gradient method for composite convex minimization," LIDAM Reprints CORE 2975, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   3. Abbaszadehpeivasti, Hadi & de Klerk, Etienne & Zamani, Moslem, 2022. "The exact worst-case convergence rate of the gradient method with fixed step lengths for L-smooth functions," Other publications TiSEM 061688c6-f97c-4024-bb5b-1, Tilburg University, School of Economics and Management.
   4. Roland Hildebrand, 2021. "Optimal step length for the Newton method: case of self-concordant functions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 94(2), pages 253-279, October.
   5. Sandra S. Y. Tan & Antonios Varvitsiotis & Vincent Y. F. Tan, 2021. "Analysis of Optimization Algorithms via Sum-of-Squares," Journal of Optimization Theory and Applications, Springer, vol. 190(1), pages 56-81, July.

10. Taylor, A. & Hendrickx, J. & Glineur, F., 2015. "Smooth Strongly Convex Interpolation and Exact Worst-case Performance of First-order Methods," LIDAM Discussion Papers CORE 2015013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Adrien B. TAYLOR & Julien M. HENDRICKX & François GLINEUR, 2017. "Smooth strongly convex interpolation and exact worst-case performance of first-order methods," LIDAM Reprints CORE 2813, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact Worst-Case Convergence Rates of the Proximal Gradient Method for Composite Convex Minimization," Journal of Optimization Theory and Applications, Springer, vol. 178(2), pages 455-476, August.
       • Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact worst-case convergence rates of the proximal gradient method for composite convex minimization," LIDAM Reprints CORE 2975, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Rieger, Janosch & Tam, Matthew K., 2020. "Backward-Forward-Reflected-Backward Splitting for Three Operator Monotone Inclusions," Applied Mathematics and Computation, Elsevier, vol. 381(C).
    3. Donghwan Kim & Jeffrey A. Fessler, 2021. "Optimizing the Efficiency of First-Order Methods for Decreasing the Gradient of Smooth Convex Functions," Journal of Optimization Theory and Applications, Springer, vol. 188(1), pages 192-219, January.
    4. Abbaszadehpeivasti, Hadi & de Klerk, Etienne & Zamani, Moslem, 2022. "The exact worst-case convergence rate of the gradient method with fixed step lengths for L-smooth functions," Other publications TiSEM 061688c6-f97c-4024-bb5b-1, Tilburg University, School of Economics and Management.
    5. Adrien B. TAYLOR & Julien M. HENDRICKX & François GLINEUR, 2017. "Exact worst-case performance of first-order methods for composite convex optimization," LIDAM Reprints CORE 2875, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • TAYLOR, Adrien B. & HENDRICKX, Julien M. & François GLINEUR, 2016. "Exact worst-case performance of first-order methods for composite convex optimization," LIDAM Discussion Papers CORE 2016052, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Sandra S. Y. Tan & Antonios Varvitsiotis & Vincent Y. F. Tan, 2021. "Analysis of Optimization Algorithms via Sum-of-Squares," Journal of Optimization Theory and Applications, Springer, vol. 190(1), pages 56-81, July.
    7. Vrins, F. & Jeanblanc, M., 2015. "The [phi]-Martingale," LIDAM Discussion Papers CORE 2015022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Ernest K. Ryu & Bằng Công Vũ, 2020. "Finding the Forward-Douglas–Rachford-Forward Method," Journal of Optimization Theory and Applications, Springer, vol. 184(3), pages 858-876, March.

11. Gillis, Nicolas & Glineur, François & Tuyttens, Daniel & Vandaele, Arnaud, 2015. "Heuristics for exact nonnegative matrix factorization," LIDAM Discussion Papers CORE 2015006, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • VANDAELE, Arnaud & GILLIS, Nicolas & GLINEUR, François & TUYTTENS, Daniel, 2016. "Heuristics for Exact Nonnegative Matrix Factorization," LIDAM Reprints CORE 2737, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Melisew Tefera Belachew & Nicolas Gillis, 2017. "Solving the Maximum Clique Problem with Symmetric Rank-One Non-negative Matrix Approximation," Journal of Optimization Theory and Applications, Springer, vol. 173(1), pages 279-296, April.
    2. Veit Elser, 2017. "Matrix product constraints by projection methods," Journal of Global Optimization, Springer, vol. 68(2), pages 329-355, June.
    3. Arnaud Vandaele & François Glineur & Nicolas Gillis, 2018. "Algorithms for positive semidefinite factorization," Computational Optimization and Applications, Springer, vol. 71(1), pages 193-219, September.
    4. PESTIEAU, Pierre & NISHIMURA, Yukihiro, 2016. "Efficient Taxation with Differential Risks of Dependence and Mortality," LIDAM Reprints CORE 2749, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • Nishimura, Y. & Pestieau, P., 2015. "Efficient taxation with differential risks of dependence and mortality," LIDAM Discussion Papers CORE 2015018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • Yukihiro Nishimura & Pierre Pestieau, 2016. "Efficient taxation with differential risks of dependence and mortality," Economics Bulletin, AccessEcon, vol. 36(1), pages 52-57.

12. POMPILI, Filippo & GILLIS, Nicolas & ABSIL, Pierre-Antoine & GLINEUR, François, 2014. "Two algorithms for orthogonal nonnegative matrix factorization with application to clusterin," LIDAM Reprints CORE 2581, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Hiroyasu Abe & Hiroshi Yadohisa, 2019. "Orthogonal nonnegative matrix tri-factorization based on Tweedie distributions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(4), pages 825-853, December.
    2. Ja’far Dehghanpour-Sahron & Nezam Mahdavi-Amiri, 2021. "A competitive optimization approach for data clustering and orthogonal non-negative matrix factorization," 4OR, Springer, vol. 19(4), pages 473-499, December.
    3. Masoud Ahookhosh & Le Thi Khanh Hien & Nicolas Gillis & Panagiotis Patrinos, 2021. "Multi-block Bregman proximal alternating linearized minimization and its application to orthogonal nonnegative matrix factorization," Computational Optimization and Applications, Springer, vol. 79(3), pages 681-715, July.

13. GILLIS, Nicolas & GLINEUR, François, 2014. "A continuous characterization of the maximum-edge biclique problem," LIDAM Reprints CORE 2567, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Nicolas Gillis & François Glineur, 2014. "A continuous characterization of the maximum-edge biclique problem," Journal of Global Optimization, Springer, vol. 58(3), pages 439-464, March.

    Cited by:

    1. Melisew Tefera Belachew & Nicolas Gillis, 2017. "Solving the Maximum Clique Problem with Symmetric Rank-One Non-negative Matrix Approximation," Journal of Optimization Theory and Applications, Springer, vol. 173(1), pages 279-296, April.

14. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2013. "First-order methods with inexact oracle: the strongly convex case," LIDAM Discussion Papers CORE 2013016, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Masaru Ito, 2016. "New results on subgradient methods for strongly convex optimization problems with a unified analysis," Computational Optimization and Applications, Springer, vol. 65(1), pages 127-172, September.
    2. Masoud Ahookhosh, 2019. "Accelerated first-order methods for large-scale convex optimization: nearly optimal complexity under strong convexity," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(3), pages 319-353, June.
    3. WANG, Kent & WANG, Shin-Huei & PAN, Zheyao, 2013. "Can federal reserve policy deviation explain response patterns of financial markets over time?," LIDAM Discussion Papers CORE 2013029, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

15. WANG, Tao & GLINEUR, François & LOUVEAUX, Jérôme & VANDENDORPE, Luc, 2013. "Weighted sum rate maximization for downlink OFDMA with subcarrier-pair basded opportunistic DF relaying," LIDAM Reprints CORE 2566, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Omar A. Elgendy & Mahmoud H. Ismail & Khaled M. F. Elsayed, 2018. "Radio resource management for LTE-A relay-enhanced cells with spatial reuse and max–min fairness," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 68(4), pages 643-655, August.

16. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2013. "Intermediate gradient methods for smooth convex problems with inexact oracle," LIDAM Discussion Papers CORE 2013017, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Nguyen Thang Dao & Julio Dávila, 2013. "Can geography lock a society in stagnation?," Documents de travail du Centre d'Economie de la Sorbonne 13037, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
       • DAO, Nguyen-Thang & DAVILA, Julio, 2013. "Can geography lock a society in stagnation?," LIDAM Discussion Papers CORE 2013030, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • Nguyen Thang Dao & Julio Dávila, 2013. "Can geography lock a society in stagnation?," Post-Print halshs-03096549, HAL.
       • DAO, Nguyen Thang & DAVILA, Julio, 2013. "Can geography lock a society in stagnation?," LIDAM Reprints CORE 2491, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • Nguyen Thang Dao & Julio Davila, 2013. "Can geography lock a society in stagnation?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00824847, HAL.
       • Dao, Nguyen Thang & Dávila, Julio, 2013. "Can geography lock a society in stagnation?," Economics Letters, Elsevier, vol. 120(3), pages 442-446.
       • Nguyen Thang Dao & Julio Davila, 2013. "Can geography lock a society in stagnation?," Post-Print halshs-00824847, HAL.
    2. Rachael Tappenden & Peter Richtárik & Jacek Gondzio, 2016. "Inexact Coordinate Descent: Complexity and Preconditioning," Journal of Optimization Theory and Applications, Springer, vol. 170(1), pages 144-176, July.
    3. Kimon Fountoulakis & Rachael Tappenden, 2018. "A flexible coordinate descent method," Computational Optimization and Applications, Springer, vol. 70(2), pages 351-394, June.
    4. Pavel Dvurechensky & Alexander Gasnikov, 2016. "Stochastic Intermediate Gradient Method for Convex Problems with Stochastic Inexact Oracle," Journal of Optimization Theory and Applications, Springer, vol. 171(1), pages 121-145, October.
    5. WANG, Kent & WANG, Shin-Huei & PAN, Zheyao, 2013. "Can federal reserve policy deviation explain response patterns of financial markets over time?," LIDAM Discussion Papers CORE 2013029, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

17. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2012. "Double smoothing technique for large-scale linearly constrained convex optimization," LIDAM Reprints CORE 2423, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Pavel Dvurechensky & Yurii Nesterov & Vladimir Spokoiny, 2015. "Primal-Dual Methods for Solving Infinite-Dimensional Games," Journal of Optimization Theory and Applications, Springer, vol. 166(1), pages 23-51, July.
    2. Radu Boţ & Christopher Hendrich, 2015. "A variable smoothing algorithm for solving convex optimization problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(1), pages 124-150, April.
    3. Radu Boţ & Christopher Hendrich, 2013. "A double smoothing technique for solving unconstrained nondifferentiable convex optimization problems," Computational Optimization and Applications, Springer, vol. 54(2), pages 239-262, March.
    4. Stefan Richter & Colin Jones & Manfred Morari, 2013. "Certification aspects of the fast gradient method for solving the dual of parametric convex programs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(3), pages 305-321, June.
    5. Taylor, A. & Hendrickx, J. & Glineur, F., 2015. "Smooth Strongly Convex Interpolation and Exact Worst-case Performance of First-order Methods," LIDAM Discussion Papers CORE 2015013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • Adrien B. TAYLOR & Julien M. HENDRICKX & François GLINEUR, 2017. "Smooth strongly convex interpolation and exact worst-case performance of first-order methods," LIDAM Reprints CORE 2813, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Adrien B. TAYLOR & Julien M. HENDRICKX & François GLINEUR, 2017. "Exact worst-case performance of first-order methods for composite convex optimization," LIDAM Reprints CORE 2875, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • TAYLOR, Adrien B. & HENDRICKX, Julien M. & François GLINEUR, 2016. "Exact worst-case performance of first-order methods for composite convex optimization," LIDAM Discussion Papers CORE 2016052, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2013. "Intermediate gradient methods for smooth convex problems with inexact oracle," LIDAM Discussion Papers CORE 2013017, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Masoud Ahookhosh & Arnold Neumaier, 2018. "Solving structured nonsmooth convex optimization with complexity $$\mathcal {O}(\varepsilon ^{-1/2})$$ O ( ε - 1 / 2 )," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 110-145, April.
    9. Quoc Tran-Dinh, 2017. "Adaptive smoothing algorithms for nonsmooth composite convex minimization," Computational Optimization and Applications, Springer, vol. 66(3), pages 425-451, April.
    10. Jueyou Li & Guo Chen & Zhaoyang Dong & Zhiyou Wu, 2016. "A fast dual proximal-gradient method for separable convex optimization with linear coupled constraints," Computational Optimization and Applications, Springer, vol. 64(3), pages 671-697, July.

18. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2011. "First-order methods of smooth convex optimization with inexact oracle," LIDAM Discussion Papers CORE 2011002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2014. "First-order methods of smooth convex optimization with inexact oracle," LIDAM Reprints CORE 2594, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Xuexue Zhang & Sanyang Liu & Nannan Zhao, 2023. "An Extended Gradient Method for Smooth and Strongly Convex Functions," Mathematics, MDPI, vol. 11(23), pages 1-14, November.
    2. DEVOLDER, Olivier, 2011. "Stochastic first order methods in smooth convex optimization," LIDAM Discussion Papers CORE 2011070, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Chengjing Wang & Peipei Tang, 2017. "A primal majorized semismooth Newton-CG augmented Lagrangian method for large-scale linearly constrained convex programming," Computational Optimization and Applications, Springer, vol. 68(3), pages 503-532, December.
    4. Tiantian Zhao & Wei Hong Yang, 2023. "A Nonlinear Conjugate Gradient Method Using Inexact First-Order Information," Journal of Optimization Theory and Applications, Springer, vol. 198(2), pages 502-530, August.
    5. Julian Rasch & Antonin Chambolle, 2020. "Inexact first-order primal–dual algorithms," Computational Optimization and Applications, Springer, vol. 76(2), pages 381-430, June.
    6. Liam Madden & Stephen Becker & Emiliano Dall’Anese, 2021. "Bounds for the Tracking Error of First-Order Online Optimization Methods," Journal of Optimization Theory and Applications, Springer, vol. 189(2), pages 437-457, May.
    7. Ion Necoara, 2021. "General Convergence Analysis of Stochastic First-Order Methods for Composite Optimization," Journal of Optimization Theory and Applications, Springer, vol. 189(1), pages 66-95, April.
    8. Stefan Richter & Colin Jones & Manfred Morari, 2013. "Certification aspects of the fast gradient method for solving the dual of parametric convex programs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(3), pages 305-321, June.
    9. Rachael Tappenden & Peter Richtárik & Jacek Gondzio, 2016. "Inexact Coordinate Descent: Complexity and Preconditioning," Journal of Optimization Theory and Applications, Springer, vol. 170(1), pages 144-176, July.
    10. Fedor Stonyakin & Ilya Kuruzov & Boris Polyak, 2023. "Stopping Rules for Gradient Methods for Non-convex Problems with Additive Noise in Gradient," Journal of Optimization Theory and Applications, Springer, vol. 198(2), pages 531-551, August.
    11. Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact Worst-Case Convergence Rates of the Proximal Gradient Method for Composite Convex Minimization," Journal of Optimization Theory and Applications, Springer, vol. 178(2), pages 455-476, August.
        • Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact worst-case convergence rates of the proximal gradient method for composite convex minimization," LIDAM Reprints CORE 2975, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2013. "First-order methods with inexact oracle: the strongly convex case," LIDAM Discussion Papers CORE 2013016, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Fedor Stonyakin & Alexander Gasnikov & Pavel Dvurechensky & Alexander Titov & Mohammad Alkousa, 2022. "Generalized Mirror Prox Algorithm for Monotone Variational Inequalities: Universality and Inexact Oracle," Journal of Optimization Theory and Applications, Springer, vol. 194(3), pages 988-1013, September.
    14. NESTEROV, Yurii, 2013. "Universal gradient methods for convex optimization problems," LIDAM Discussion Papers CORE 2013026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Anastasis Kratsios, 2019. "Partial Uncertainty and Applications to Risk-Averse Valuation," Papers 1909.13610, arXiv.org, revised Oct 2019.
    16. Kimon Fountoulakis & Rachael Tappenden, 2018. "A flexible coordinate descent method," Computational Optimization and Applications, Springer, vol. 70(2), pages 351-394, June.
    17. Pavel Dvurechensky & Alexander Gasnikov, 2016. "Stochastic Intermediate Gradient Method for Convex Problems with Stochastic Inexact Oracle," Journal of Optimization Theory and Applications, Springer, vol. 171(1), pages 121-145, October.
    18. Adrien B. TAYLOR & Julien M. HENDRICKX & François GLINEUR, 2017. "Exact worst-case performance of first-order methods for composite convex optimization," LIDAM Reprints CORE 2875, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
        • TAYLOR, Adrien B. & HENDRICKX, Julien M. & François GLINEUR, 2016. "Exact worst-case performance of first-order methods for composite convex optimization," LIDAM Discussion Papers CORE 2016052, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2013. "Intermediate gradient methods for smooth convex problems with inexact oracle," LIDAM Discussion Papers CORE 2013017, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    20. Masoud Ahookhosh & Arnold Neumaier, 2018. "Solving structured nonsmooth convex optimization with complexity $$\mathcal {O}(\varepsilon ^{-1/2})$$ O ( ε - 1 / 2 )," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 110-145, April.
    21. Renato D. C. Monteiro & Camilo Ortiz & Benar F. Svaiter, 2016. "An adaptive accelerated first-order method for convex optimization," Computational Optimization and Applications, Springer, vol. 64(1), pages 31-73, May.
    22. Jueyou Li & Zhiyou Wu & Changzhi Wu & Qiang Long & Xiangyu Wang, 2016. "An Inexact Dual Fast Gradient-Projection Method for Separable Convex Optimization with Linear Coupled Constraints," Journal of Optimization Theory and Applications, Springer, vol. 168(1), pages 153-171, January.
    23. Masaru Ito, 2016. "New results on subgradient methods for strongly convex optimization problems with a unified analysis," Computational Optimization and Applications, Springer, vol. 65(1), pages 127-172, September.
    24. Masoud Ahookhosh, 2019. "Accelerated first-order methods for large-scale convex optimization: nearly optimal complexity under strong convexity," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(3), pages 319-353, June.
    25. Immanuel M. Bomze & Francesco Rinaldi & Damiano Zeffiro, 2021. "Frank–Wolfe and friends: a journey into projection-free first-order optimization methods," 4OR, Springer, vol. 19(3), pages 313-345, September.
    26. J. O. Royset & E. Y. Pee, 2012. "Rate of Convergence Analysis of Discretization and Smoothing Algorithms for Semiinfinite Minimax Problems," Journal of Optimization Theory and Applications, Springer, vol. 155(3), pages 855-882, December.
    27. Le Thi Khanh Hien & Cuong V. Nguyen & Huan Xu & Canyi Lu & Jiashi Feng, 2019. "Accelerated Randomized Mirror Descent Algorithms for Composite Non-strongly Convex Optimization," Journal of Optimization Theory and Applications, Springer, vol. 181(2), pages 541-566, May.
    28. Tianxiao Sun & Ion Necoara & Quoc Tran-Dinh, 2020. "Composite convex optimization with global and local inexact oracles," Computational Optimization and Applications, Springer, vol. 76(1), pages 69-124, May.

19. GILLIS, Nicolas & GLINEUR, François, 2011. "Accelerated multiplicative updates and hierarchical als algorithms for nonnegative matrix factorization," LIDAM Discussion Papers CORE 2011030, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • GILLIS, Nicolas & GLINEUR, François, 2012. "Accelerated multiplicative updates and hierarchical ALS algorithms for nonnegative matrix factorization," LIDAM Reprints CORE 2389, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. VANDAELE, Arnaud & GILLIS, Nicolas & GLINEUR, François & TUYTTENS, Daniel, 2016. "Heuristics for Exact Nonnegative Matrix Factorization," LIDAM Reprints CORE 2737, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • Gillis, Nicolas & Glineur, François & Tuyttens, Daniel & Vandaele, Arnaud, 2015. "Heuristics for exact nonnegative matrix factorization," LIDAM Discussion Papers CORE 2015006, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. GAHUNGU, Joachim & SMEERS, Yves, 2011. "A real options model for electricity capacity expansion," LIDAM Discussion Papers CORE 2011044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Norikazu Takahashi & Ryota Hibi, 2014. "Global convergence of modified multiplicative updates for nonnegative matrix factorization," Computational Optimization and Applications, Springer, vol. 57(2), pages 417-440, March.
    4. Lei Yang, 2024. "Proximal Gradient Method with Extrapolation and Line Search for a Class of Non-convex and Non-smooth Problems," Journal of Optimization Theory and Applications, Springer, vol. 200(1), pages 68-103, January.
    5. VAN VYVE, Mathieu, 2011. "Linear prices for non-convex electricity markets: models and algorithms," LIDAM Discussion Papers CORE 2011050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Augusto Ruperez Micola & Albert Banal-Estanol, 2011. "Production intermittence in sport markets," DEM Discussion Paper Series 11-15, Department of Economics at the University of Luxembourg.
       • GABSZEWICZ, Jean J. & VAN YPERSELE, Tanguy & ZANAJ, Skerdilajda, 2011. "Does the seller of a house facing a large number of buyers always decrease its price when its first offer is rejected?," LIDAM Discussion Papers CORE 2011049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Arnaud Vandaele & François Glineur & Nicolas Gillis, 2018. "Algorithms for positive semidefinite factorization," Computational Optimization and Applications, Springer, vol. 71(1), pages 193-219, September.
    8. Jingu Kim & Yunlong He & Haesun Park, 2014. "Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework," Journal of Global Optimization, Springer, vol. 58(2), pages 285-319, February.
    9. Andrej Čopar & Blaž Zupan & Marinka Zitnik, 2019. "Fast optimization of non-negative matrix tri-factorization," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-15, June.
    10. CHANDER, Parkash & TULKENS, Henry, 2011. "The kyoto Protocol, the Copenhagen Accord, the Cancun Agreements, and beyond: an economic and game theoretical exploration and interpretation," LIDAM Discussion Papers CORE 2011051, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Rundong Du & Da Kuang & Barry Drake & Haesun Park, 2017. "DC-NMF: nonnegative matrix factorization based on divide-and-conquer for fast clustering and topic modeling," Journal of Global Optimization, Springer, vol. 68(4), pages 777-798, August.
    12. Duy Khuong Nguyen & Tu Bao Ho, 2017. "Accelerated parallel and distributed algorithm using limited internal memory for nonnegative matrix factorization," Journal of Global Optimization, Springer, vol. 68(2), pages 307-328, June.
    13. Takehiro Sano & Tsuyoshi Migita & Norikazu Takahashi, 2022. "A novel update rule of HALS algorithm for nonnegative matrix factorization and Zangwill’s global convergence," Journal of Global Optimization, Springer, vol. 84(3), pages 755-781, November.

20. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2010. "Solving infinite-dimensional optimization problems by polynomial approximation," LIDAM Discussion Papers CORE 2010029, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2010. "Solving infinite-dimensional optimizaiton problems by polynomial approximation," LIDAM Reprints CORE 2241, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Jubril, A.M. & Olaniyan, O.A. & Komolafe, O.A. & Ogunbona, P.O., 2014. "Economic-emission dispatch problem: A semi-definite programming approach," Applied Energy, Elsevier, vol. 134(C), pages 446-455.
    2. Kristina Rognlien Dahl, 2019. "A convex duality approach for pricing contingent claims under partial information and short selling constraints," Papers 1902.10492, arXiv.org.
    3. Kristina Rognlien Dahl, 2019. "Management of a hydropower system via convex duality," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(1), pages 43-71, February.

21. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2010. "Double smoothing technique for infinite-dimensional optimization problems with applications to optimal control," LIDAM Discussion Papers CORE 2010034, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2011. "First-order methods of smooth convex optimization with inexact oracle," LIDAM Discussion Papers CORE 2011002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2014. "First-order methods of smooth convex optimization with inexact oracle," LIDAM Reprints CORE 2594, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

22. GILLIS, Nicolas & GLINEUR, François, 2010. "Low-rank matrix approximation with weights or missing data is NP-hard," LIDAM Discussion Papers CORE 2010075, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • GILLIS, Nicolas & GLINEUR, François, 2011. "Low-rank matrix approximation with weights or missing data is NP-hard," LIDAM Reprints CORE 2382, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Nicolas Gillis & Stephen A. Vavasis, 2018. "On the Complexity of Robust PCA and ℓ 1 -Norm Low-Rank Matrix Approximation," Mathematics of Operations Research, INFORMS, vol. 43(4), pages 1072-1084, November.
    2. Qinghua Wu & Yang Wang & Fred Glover, 2020. "Advanced Tabu Search Algorithms for Bipartite Boolean Quadratic Programs Guided by Strategic Oscillation and Path Relinking," INFORMS Journal on Computing, INFORMS, vol. 32(1), pages 74-89, January.
    3. Gillard, Jonathan & Usevich, Konstantin, 2018. "Structured low-rank matrix completion for forecasting in time series analysis," International Journal of Forecasting, Elsevier, vol. 34(4), pages 582-597.
    4. Glover, Fred & Ye, Tao & Punnen, Abraham P. & Kochenberger, Gary, 2015. "Integrating tabu search and VLSN search to develop enhanced algorithms: A case study using bipartite boolean quadratic programs," European Journal of Operational Research, Elsevier, vol. 241(3), pages 697-707.
    5. Namgil Lee & Jong-Min Kim, 2018. "Block tensor train decomposition for missing data estimation," Statistical Papers, Springer, vol. 59(4), pages 1283-1305, December.
    6. Zhikai Yang & Le Han, 2023. "A global exact penalty for rank-constrained optimization problem and applications," Computational Optimization and Applications, Springer, vol. 84(2), pages 477-508, March.

23. BOUS, Géraldine & FORTEMPS, Philippe & GLINEUR, François & PIRLOT, Marc, 2010. "ACUTA: a novel method for eliciting additive value functions on the basis of holistic preference statements," LIDAM Reprints CORE 2243, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Bous, Géraldine & Fortemps, Philippe & Glineur, François & Pirlot, Marc, 2010. "ACUTA: A novel method for eliciting additive value functions on the basis of holistic preference statements," European Journal of Operational Research, Elsevier, vol. 206(2), pages 435-444, October.

    Cited by:

    1. Sobrie, Olivier & Gillis, Nicolas & Mousseau, Vincent & Pirlot, Marc, 2018. "UTA-poly and UTA-splines: Additive value functions with polynomial marginals," European Journal of Operational Research, Elsevier, vol. 264(2), pages 405-418.
    2. Kadziński, Miłosz & Wójcik, Michał & Ciomek, Krzysztof, 2022. "Review and experimental comparison of ranking and choice procedures for constructing a univocal recommendation in a preference disaggregation setting," Omega, Elsevier, vol. 113(C).
    3. Vetschera, Rudolf, 2017. "Deriving rankings from incomplete preference information: A comparison of different approaches," European Journal of Operational Research, Elsevier, vol. 258(1), pages 244-253.
    4. Reimann, Olivier & Schumacher, Christian & Vetschera, Rudolf, 2017. "How well does the OWA operator represent real preferences?," European Journal of Operational Research, Elsevier, vol. 258(3), pages 993-1003.
    5. Bouchery, Yann & Ghaffari, Asma & Jemai, Zied & Dallery, Yves, 2012. "Including sustainability criteria into inventory models," European Journal of Operational Research, Elsevier, vol. 222(2), pages 229-240.
    6. Dorota Górecka & Ewa Roszkowska & Tomasz Wachowicz, 2016. "The MARS Approach in the Verbal and Holistic Evaluation of the Negotiation Template," Group Decision and Negotiation, Springer, vol. 25(6), pages 1097-1136, November.
    7. Hurson, Christian & Siskos, Yannis, 2014. "A synergy of multicriteria techniques to assess additive value models," European Journal of Operational Research, Elsevier, vol. 238(2), pages 540-551.
    8. Kadziński, Miłosz & Greco, Salvatore & Słowiński, Roman, 2012. "Selection of a representative value function in robust multiple criteria ranking and choice," European Journal of Operational Research, Elsevier, vol. 217(3), pages 541-553.
    9. Podinovski, Vladislav V., 2020. "Maximum likelihood solutions for multicriterial choice problems," European Journal of Operational Research, Elsevier, vol. 286(1), pages 299-308.
    10. Khaled, Oumaima & Minoux, Michel & Mousseau, Vincent & Michel, Stéphane & Ceugniet, Xavier, 2018. "A multi-criteria repair/recovery framework for the tail assignment problem in airlines," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 137-151.
    11. Tomasz Wachowicz & Gregory E. Kersten & Ewa Roszkowska, 2019. "How do I tell you what I want? Agent’s interpretation of principal’s preferences and its impact on understanding the negotiation process and outcomes," Operational Research, Springer, vol. 19(4), pages 993-1032, December.
    12. Sarfaraz Hashemkhani Zolfani & Edmundas Kazimieras Zavadskas & Payam Khazaelpour & Fausto Cavallaro, 2018. "The Multi-Aspect Criterion in the PMADM Outline and Its Possible Application to Sustainability Assessment," Sustainability, MDPI, vol. 10(12), pages 1-15, November.
    13. Ghaderi, Mohammad & Ruiz, Francisco & Agell, Núria, 2017. "A linear programming approach for learning non-monotonic additive value functions in multiple criteria decision aiding," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1073-1084.
    14. Bagherzadeh, Mehdi & Ghaderi, Mohammad & Fernandez, Anne-Sophie, 2022. "Coopetition for innovation - the more, the better? An empirical study based on preference disaggregation analysis," European Journal of Operational Research, Elsevier, vol. 297(2), pages 695-708.
    15. Miłosz Kadziński & Salvatore Greco & Roman Słowiński, 2013. "Selection of a Representative Value Function for Robust Ordinal Regression in Group Decision Making," Group Decision and Negotiation, Springer, vol. 22(3), pages 429-462, May.
    16. Cinelli, Marco & Kadziński, Miłosz & Miebs, Grzegorz & Gonzalez, Michael & Słowiński, Roman, 2022. "Recommending multiple criteria decision analysis methods with a new taxonomy-based decision support system," European Journal of Operational Research, Elsevier, vol. 302(2), pages 633-651.
    17. Nguyen, Duy Van, 2013. "Global maximization of UTA functions in multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 228(2), pages 397-404.
    18. Ciomek, Krzysztof & Ferretti, Valentina & Kadzinski, Milosz, 2018. "Predictive analytics and disused railways requalification: insights from a Post Factum Analysis perspective," LSE Research Online Documents on Economics 85922, London School of Economics and Political Science, LSE Library.
    19. Guo, Mengzhuo & Liao, Xiuwu & Liu, Jiapeng & Zhang, Qingpeng, 2020. "Consumer preference analysis: A data-driven multiple criteria approach integrating online information," Omega, Elsevier, vol. 96(C).
    20. Khaled Belahcène & Vincent Mousseau & Wassila Ouerdane & Marc Pirlot & Olivier Sobrie, 2023. "Multiple criteria sorting models and methods—Part I: survey of the literature," 4OR, Springer, vol. 21(1), pages 1-46, March.
    21. Paula Sarabando & Luís C. Dias & Rudolf Vetschera, 2013. "Mediation with Incomplete Information: Approaches to Suggest Potential Agreements," Group Decision and Negotiation, Springer, vol. 22(3), pages 561-597, May.
    22. Zheng, Jun & Lienert, Judit, 2018. "Stakeholder interviews with two MAVT preference elicitation philosophies in a Swiss water infrastructure decision: Aggregation using SWING-weighting and disaggregation using UTAGMS," European Journal of Operational Research, Elsevier, vol. 267(1), pages 273-287.
    23. Ferretti, Valentina & Liu, Jun & Mousseau, V & Ouerdane, W, 2017. "Reference-based ranking procedure for environmental decision making: insights from an ex-post analysis," LSE Research Online Documents on Economics 85933, London School of Economics and Political Science, LSE Library.
    24. Bottomley, Paul A. & Doyle, John R., 2013. "Comparing the validity of numerical judgements elicited by direct rating and point allocation: Insights from objectively verifiable perceptual tasks," European Journal of Operational Research, Elsevier, vol. 228(1), pages 148-157.
    25. Wachowicz, Tomasz & Roszkowska, Ewa, 2022. "Can holistic declaration of preferences improve a negotiation offer scoring system?," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1018-1032.
    26. Doumpos, Michael & Zopounidis, Constantin & Galariotis, Emilios, 2014. "Inferring robust decision models in multicriteria classification problems: An experimental analysis," European Journal of Operational Research, Elsevier, vol. 236(2), pages 601-611.
    27. Gabriela D. Oliveira & Luis C. Dias, 2020. "The potential learning effect of a MCDA approach on consumer preferences for alternative fuel vehicles," Annals of Operations Research, Springer, vol. 293(2), pages 767-787, October.
    28. Christoph Graf & Rudolf Vetschera & Yingchao Zhang, 2013. "Parameters of social preference functions: measurement and external validity," Theory and Decision, Springer, vol. 74(3), pages 357-382, March.
    29. Kadziński, Miłosz & Ciomek, Krzysztof & Słowiński, Roman, 2015. "Modeling assignment-based pairwise comparisons within integrated framework for value-driven multiple criteria sorting," European Journal of Operational Research, Elsevier, vol. 241(3), pages 830-841.

24. GILLIS, Nicolas & GLINEUR, François, 2010. "On the geometric interpretation of the nonnegative rank," LIDAM Discussion Papers CORE 2010051, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • GILLIS, Nicolas & GLINEUR, François, 2012. "On the geometric interpretation of the nonnegative rank," LIDAM Reprints CORE 2439, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen V.K. Rombouts, 2011. "The Contribution of Structural Break Models to Forecasting Macroeconomic Series," Working Paper series 38_11, Rimini Centre for Economic Analysis.
       • Bauwens, Luc & Korobilis, Dimitris & Koop, Gary & Rombouts, Jeroen V.K., 2011. "A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models," SIRE Discussion Papers 2011-25, Scottish Institute for Research in Economics (SIRE).
       • Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen Rombouts, 2011. "A Comparison of Forecasting Procedures For Macroeconomic Series: The Contribution of Structural Break Models," CIRANO Working Papers 2011s-13, CIRANO.
       • Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen V.K. Rombouts, 2015. "The Contribution of Structural Break Models to Forecasting Macroeconomic Series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 596-620, June.
       • Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen Rombouts, 2011. "A comparison of Forecasting Procedures for Macroeconomic Series: The Contribution of Structural Break Models," Working Papers 1113, University of Strathclyde Business School, Department of Economics.
       • Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen V.K. Rombouts, 2011. "A Comparison of Forecasting Procedures for Macroeconomic Series: the Contribution of Structural Break Models," Cahiers de recherche 1104, CIRPEE.
       • BAUWENS, Luc & KOOP, Gary & KOROBILIS, Dimitris & ROMBOUTS, Jeroen, 2015. "The Contribution of Structural Break Models to Forecating Macroeconomic Series," LIDAM Reprints CORE 2651, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • BAUWENS, Luc & KOOP, Gary & KOROBILIS, Dimitris & ROMBOUTS, Jeroen V. K., 2011. "A comparison of forecasting procedures for macroeconomic series: the contribution of structural break models," LIDAM Discussion Papers CORE 2011003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. VANDAELE, Arnaud & GILLIS, Nicolas & GLINEUR, François & TUYTTENS, Daniel, 2016. "Heuristics for Exact Nonnegative Matrix Factorization," LIDAM Reprints CORE 2737, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • Gillis, Nicolas & Glineur, François & Tuyttens, Daniel & Vandaele, Arnaud, 2015. "Heuristics for exact nonnegative matrix factorization," LIDAM Discussion Papers CORE 2015006, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2011. "First-order methods of smooth convex optimization with inexact oracle," LIDAM Discussion Papers CORE 2011002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2014. "First-order methods of smooth convex optimization with inexact oracle," LIDAM Reprints CORE 2594, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Veit Elser, 2017. "Matrix product constraints by projection methods," Journal of Global Optimization, Springer, vol. 68(2), pages 329-355, June.
    5. NESTEROV, Yurii, 2011. "Random gradient-free minimization of convex functions," LIDAM Discussion Papers CORE 2011001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. AGRELL, Per & KASPERZEC, Roman, 2010. "Dynamic joint investments in supply chains under information asymmetry," LIDAM Discussion Papers CORE 2010085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Gribling, Sander & Laat, David de & Laurent, Monique, 2017. "Lower Bounds on Matrix Factorization Ranks via Noncommutative Polynomial Optimization," Other publications TiSEM 2dddf156-3d4b-4936-bf02-a, Tilburg University, School of Economics and Management.

25. GILLIS, Nicolas & GLINEUR, François, 2010. "A multilevel approach for nonnegative matrix factorization," LIDAM Discussion Papers CORE 2010047, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • GILLIS, Nicolas & GLINEUR, François, 2011. "A multilevel approach for nonnegative matrix factorization," LIDAM Reprints CORE 2381, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Johannes Friedrich & Weijian Yang & Daniel Soudry & Yu Mu & Misha B Ahrens & Rafael Yuste & Darcy S Peterka & Liam Paninski, 2017. "Multi-scale approaches for high-speed imaging and analysis of large neural populations," PLOS Computational Biology, Public Library of Science, vol. 13(8), pages 1-24, August.
    2. Jingu Kim & Yunlong He & Haesun Park, 2014. "Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework," Journal of Global Optimization, Springer, vol. 58(2), pages 285-319, February.
    3. AGRELL, Per & KASPERZEC, Roman, 2010. "Dynamic joint investments in supply chains under information asymmetry," LIDAM Discussion Papers CORE 2010085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

26. DENIES, Jonathan & DEHEZ, Bruno & GLINEUR, François & BEN AHMED, Hamid, 2010. "Impact of the material distribution formalism on the efficiency of evolutionary methods for topology optimization," LIDAM Reprints CORE 2242, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Denies, J. & Ben Ahmed, H. & Dehez, B., 2013. "Optimal design of electromagnetic devices: Development of an efficient optimization tool based on smart mutation operations implemented in a genetic algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 90(C), pages 244-255.

27. GILLIS, Nicolas & GLINEUR, François, 2009. "Using underapproximations for sparse nonnegative matrix factorization," LIDAM Discussion Papers CORE 2009006, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • GILLIS, Nicolas & Glineur, François, 2010. "Using underapproximations for sparse nonnegative matrix factorization," LIDAM Reprints CORE 2187, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. GILLIS, Nicolas & GLINEUR, François, 2010. "Nonnegative factorization and the maximum edge biclique problem," LIDAM Discussion Papers CORE 2010059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • GILLIS, Nicolas & GLINEUR, François, 2008. "Nonnegative factorization and the maximum edge biclique problem," LIDAM Discussion Papers CORE 2008064, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. VANDAELE, Arnaud & GILLIS, Nicolas & GLINEUR, François & TUYTTENS, Daniel, 2016. "Heuristics for Exact Nonnegative Matrix Factorization," LIDAM Reprints CORE 2737, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • Gillis, Nicolas & Glineur, François & Tuyttens, Daniel & Vandaele, Arnaud, 2015. "Heuristics for exact nonnegative matrix factorization," LIDAM Discussion Papers CORE 2015006, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Nicolas Gillis & Stephen A. Vavasis, 2018. "On the Complexity of Robust PCA and ℓ 1 -Norm Low-Rank Matrix Approximation," Mathematics of Operations Research, INFORMS, vol. 43(4), pages 1072-1084, November.
    4. Jingu Kim & Yunlong He & Haesun Park, 2014. "Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework," Journal of Global Optimization, Springer, vol. 58(2), pages 285-319, February.

28. GILLIS, Nicolas & GLINEUR, François, 2008. "Nonnegative factorization and the maximum edge biclique problem," LIDAM Discussion Papers CORE 2008064, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • GILLIS, Nicolas & GLINEUR, François, 2010. "Nonnegative factorization and the maximum edge biclique problem," LIDAM Discussion Papers CORE 2010059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. GILLIS, Nicolas & GLINEUR, François, 2011. "Accelerated multiplicative updates and hierarchical als algorithms for nonnegative matrix factorization," LIDAM Discussion Papers CORE 2011030, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • GILLIS, Nicolas & GLINEUR, François, 2012. "Accelerated multiplicative updates and hierarchical ALS algorithms for nonnegative matrix factorization," LIDAM Reprints CORE 2389, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. GILLIS, Nicolas & GLINEUR, François, 2014. "A continuous characterization of the maximum-edge biclique problem," LIDAM Reprints CORE 2567, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • Nicolas Gillis & François Glineur, 2014. "A continuous characterization of the maximum-edge biclique problem," Journal of Global Optimization, Springer, vol. 58(3), pages 439-464, March.
    3. GILLIS, Nicolas & GLINEUR, François, 2010. "On the geometric interpretation of the nonnegative rank," LIDAM Discussion Papers CORE 2010051, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • GILLIS, Nicolas & GLINEUR, François, 2012. "On the geometric interpretation of the nonnegative rank," LIDAM Reprints CORE 2439, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. GILLIS, Nicolas & GLINEUR, François, 2011. "Low-rank matrix approximation with weights or missing data is NP-hard," LIDAM Reprints CORE 2382, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • GILLIS, Nicolas & GLINEUR, François, 2010. "Low-rank matrix approximation with weights or missing data is NP-hard," LIDAM Discussion Papers CORE 2010075, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Norikazu Takahashi & Ryota Hibi, 2014. "Global convergence of modified multiplicative updates for nonnegative matrix factorization," Computational Optimization and Applications, Springer, vol. 57(2), pages 417-440, March.
    6. Norikazu Takahashi & Jiro Katayama & Masato Seki & Jun’ichi Takeuchi, 2018. "A unified global convergence analysis of multiplicative update rules for nonnegative matrix factorization," Computational Optimization and Applications, Springer, vol. 71(1), pages 221-250, September.
    7. Jingu Kim & Yunlong He & Haesun Park, 2014. "Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework," Journal of Global Optimization, Springer, vol. 58(2), pages 285-319, February.
    8. Takehiro Sano & Tsuyoshi Migita & Norikazu Takahashi, 2022. "A novel update rule of HALS algorithm for nonnegative matrix factorization and Zangwill’s global convergence," Journal of Global Optimization, Springer, vol. 84(3), pages 755-781, November.

29. CHARES, Robert & GLINEUR, François, 2007. "An interior-point method for the single-facility location problem with mixed norms using a conic formulation," LIDAM Discussion Papers CORE 2007071, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Robert Chares & François Glineur, 2008. "An interior-point method for the single-facility location problem with mixed norms using a conic formulation," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 68(3), pages 383-405, December.
    • CHARES, Robert & GLINEUR, François, 2009. "An interior-point method for the single-facility location problem with mixed norms using a conic formulation," LIDAM Reprints CORE 2078, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Le Hien, 2015. "Differential properties of Euclidean projection onto power cone," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 82(3), pages 265-284, December.

30. GLINEUR, François & TERLAKY, Tamas, 2004. "Conic formulation for lp-norm optimization," LIDAM Reprints CORE 1726, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • F. Glineur & T. Terlaky, 2004. "Conic Formulation for l p -Norm Optimization," Journal of Optimization Theory and Applications, Springer, vol. 122(2), pages 285-307, August.

    Cited by:

    1. CHARES, Robert & GLINEUR, François, 2007. "An interior-point method for the single-facility location problem with mixed norms using a conic formulation," LIDAM Discussion Papers CORE 2007071, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • Robert Chares & François Glineur, 2008. "An interior-point method for the single-facility location problem with mixed norms using a conic formulation," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 68(3), pages 383-405, December.
       • CHARES, Robert & GLINEUR, François, 2009. "An interior-point method for the single-facility location problem with mixed norms using a conic formulation," LIDAM Reprints CORE 2078, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Yue Lu & Ching-Yu Yang & Jein-Shan Chen & Hou-Duo Qi, 2020. "The decompositions with respect to two core non-symmetric cones," Journal of Global Optimization, Springer, vol. 76(1), pages 155-188, January.
    3. Baha Alzalg, 2016. "The Algebraic Structure of the Arbitrary-Order Cone," Journal of Optimization Theory and Applications, Springer, vol. 169(1), pages 32-49, April.
    4. Jinchuan Zhou & Yu-Lin Chang & Jein-Shan Chen, 2015. "The H-differentiability and calmness of circular cone functions," Journal of Global Optimization, Springer, vol. 63(4), pages 811-833, December.
    5. GLINEUR, François & TERLAKY, Tamas, 2004. "Conic formulation for lp-norm optimization," LIDAM Reprints CORE 1726, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
       • F. Glineur & T. Terlaky, 2004. "Conic Formulation for l p -Norm Optimization," Journal of Optimization Theory and Applications, Springer, vol. 122(2), pages 285-307, August.
    6. Dávid Papp & Sercan Yıldız, 2022. "Alfonso: Matlab Package for Nonsymmetric Conic Optimization," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 11-19, January.
    7. Krokhmal, Pavlo A. & Soberanis, Policarpio, 2010. "Risk optimization with p-order conic constraints: A linear programming approach," European Journal of Operational Research, Elsevier, vol. 201(3), pages 653-671, March.

Articles

1. Arnaud Vandaele & François Glineur & Nicolas Gillis, 2018. "Algorithms for positive semidefinite factorization," Computational Optimization and Applications, Springer, vol. 71(1), pages 193-219, September.

   Cited by:

   1. Gribling, Sander, 2019. "Applications of optimization to factorization ranks and quantum information theory," Other publications TiSEM 5c681ab9-2344-4a07-b818-f, Tilburg University, School of Economics and Management.
   2. Shun Arahata & Takayuki Okuno & Akiko Takeda, 2023. "Complexity analysis of interior-point methods for second-order stationary points of nonlinear semidefinite optimization problems," Computational Optimization and Applications, Springer, vol. 86(2), pages 555-598, November.

2. Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact Worst-Case Convergence Rates of the Proximal Gradient Method for Composite Convex Minimization," Journal of Optimization Theory and Applications, Springer, vol. 178(2), pages 455-476, August.
   • Adrien B. Taylor & Julien M. Hendrickx & François Glineur, 2018. "Exact worst-case convergence rates of the proximal gradient method for composite convex minimization," LIDAM Reprints CORE 2975, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   See citations under working paper version above.
3. Ion Necoara & Yurii Nesterov & François Glineur, 2017. "Random Block Coordinate Descent Methods for Linearly Constrained Optimization over Networks," Journal of Optimization Theory and Applications, Springer, vol. 173(1), pages 227-254, April.
   • Ion NECOARA & Yurii NESTEROV & François GLINEUR, 2017. "Random block coordinate descent methods for linearly constrained optimization over networks," LIDAM Reprints CORE 2844, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   See citations under working paper version above.
4. Nicolas Gillis & François Glineur, 2014. "A continuous characterization of the maximum-edge biclique problem," Journal of Global Optimization, Springer, vol. 58(3), pages 439-464, March.
   • GILLIS, Nicolas & GLINEUR, François, 2014. "A continuous characterization of the maximum-edge biclique problem," LIDAM Reprints CORE 2567, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   See citations under working paper version above.
5. Bous, Géraldine & Fortemps, Philippe & Glineur, François & Pirlot, Marc, 2010. "ACUTA: A novel method for eliciting additive value functions on the basis of holistic preference statements," European Journal of Operational Research, Elsevier, vol. 206(2), pages 435-444, October.
   • BOUS, Géraldine & FORTEMPS, Philippe & GLINEUR, François & PIRLOT, Marc, 2010. "ACUTA: a novel method for eliciting additive value functions on the basis of holistic preference statements," LIDAM Reprints CORE 2243, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   See citations under working paper version above.
6. Robert Chares & François Glineur, 2008. "An interior-point method for the single-facility location problem with mixed norms using a conic formulation," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 68(3), pages 383-405, December.
   • CHARES, Robert & GLINEUR, François, 2007. "An interior-point method for the single-facility location problem with mixed norms using a conic formulation," LIDAM Discussion Papers CORE 2007071, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   • CHARES, Robert & GLINEUR, François, 2009. "An interior-point method for the single-facility location problem with mixed norms using a conic formulation," LIDAM Reprints CORE 2078, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   See citations under working paper version above.
7. F. Glineur & T. Terlaky, 2004. "Conic Formulation for l p -Norm Optimization," Journal of Optimization Theory and Applications, Springer, vol. 122(2), pages 285-307, August.
   • GLINEUR, François & TERLAKY, Tamas, 2004. "Conic formulation for lp-norm optimization," LIDAM Reprints CORE 1726, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   See citations under working paper version above.
8. François Glineur, 2001. "Proving Strong Duality for Geometric Optimization Using a Conic Formulation," Annals of Operations Research, Springer, vol. 105(1), pages 155-184, July.

   Cited by:

   1. CHARES, Robert & GLINEUR, François, 2007. "An interior-point method for the single-facility location problem with mixed norms using a conic formulation," LIDAM Discussion Papers CORE 2007071, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Robert Chares & François Glineur, 2008. "An interior-point method for the single-facility location problem with mixed norms using a conic formulation," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 68(3), pages 383-405, December.
      • CHARES, Robert & GLINEUR, François, 2009. "An interior-point method for the single-facility location problem with mixed norms using a conic formulation," LIDAM Reprints CORE 2078, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
   2. Qinghong Zhang & Kenneth O. Kortanek, 2019. "On a Compound Duality Classification for Geometric Programming," Journal of Optimization Theory and Applications, Springer, vol. 180(3), pages 711-728, March.
   3. Yue Lu & Ching-Yu Yang & Jein-Shan Chen & Hou-Duo Qi, 2020. "The decompositions with respect to two core non-symmetric cones," Journal of Global Optimization, Springer, vol. 76(1), pages 155-188, January.
   4. GLINEUR, François & TERLAKY, Tamas, 2004. "Conic formulation for lp-norm optimization," LIDAM Reprints CORE 1726, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • F. Glineur & T. Terlaky, 2004. "Conic Formulation for l p -Norm Optimization," Journal of Optimization Theory and Applications, Springer, vol. 122(2), pages 285-307, August.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 4 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-CMP: Computational Economics (2) 2010-10-02 2018-01-29
2. NEP-ECM: Econometrics (1) 2011-02-12
3. NEP-ORE: Operations Research (1) 2010-10-02

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