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Lectures on Convex Optimization

Citations

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Cited by:

  1. David Müller & Vladimir Shikhman, 2022. "Network manipulation algorithm based on inexact alternating minimization," Computational Management Science, Springer, vol. 19(4), pages 627-664, October.
  2. Xiaojun Zhou & Chunna Zhao & Yaqun Huang, 2023. "A Deep Learning Optimizer Based on Grünwald–Letnikov Fractional Order Definition," Mathematics, MDPI, vol. 11(2), pages 1-15, January.
  3. Shota Takahashi & Mituhiro Fukuda & Mirai Tanaka, 2022. "New Bregman proximal type algorithms for solving DC optimization problems," Computational Optimization and Applications, Springer, vol. 83(3), pages 893-931, December.
  4. Guo, Chuanyin & Song, Qiwei & Yu, Ming-Miin & Zhang, Jian, 2024. "A digital economy development index based on an improved hierarchical data envelopment analysis approach," European Journal of Operational Research, Elsevier, vol. 316(3), pages 1146-1157.
  5. Mehdi Karimi & Levent Tunçel, 2020. "Primal–Dual Interior-Point Methods for Domain-Driven Formulations," Mathematics of Operations Research, INFORMS, vol. 45(2), pages 591-621, May.
  6. Yurii Nesterov, 2021. "Superfast Second-Order Methods for Unconstrained Convex Optimization," Journal of Optimization Theory and Applications, Springer, vol. 191(1), pages 1-30, October.
  7. A. Scagliotti & P. Colli Franzone, 2022. "A piecewise conservative method for unconstrained convex optimization," Computational Optimization and Applications, Springer, vol. 81(1), pages 251-288, January.
  8. Francisco García Riesgo & Sergio Luis Suárez Gómez & Enrique Díez Alonso & Carlos González-Gutiérrez & Jesús Daniel Santos, 2021. "Fully Convolutional Approaches for Numerical Approximation of Turbulent Phases in Solar Adaptive Optics," Mathematics, MDPI, vol. 9(14), pages 1-20, July.
  9. Doikov, Nikita & Nesterov, Yurii, 2020. "Affine-invariant contracting-point methods for Convex Optimization," LIDAM Discussion Papers CORE 2020029, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  10. Pavel Shcherbakov & Mingyue Ding & Ming Yuchi, 2021. "Random Sampling Many-Dimensional Sets Arising in Control," Mathematics, MDPI, vol. 9(5), pages 1-16, March.
  11. Xin Jiang & Lieven Vandenberghe, 2022. "Bregman primal–dual first-order method and application to sparse semidefinite programming," Computational Optimization and Applications, Springer, vol. 81(1), pages 127-159, January.
  12. Fosgerau, Mogens & Melo, Emerson & Shum, Matthew & Sørensen, Jesper R.-V., 2021. "Some remarks on CCP-based estimators of dynamic models," Economics Letters, Elsevier, vol. 204(C).
  13. Insoon Yang, 2020. "A Convex Optimization Approach to Dynamic Programming in Continuous State and Action Spaces," Journal of Optimization Theory and Applications, Springer, vol. 187(1), pages 133-157, October.
  14. A. Ghaffari-Hadigheh & L. Sinjorgo & R. Sotirov, 2024. "On convergence of a q-random coordinate constrained algorithm for non-convex problems," Journal of Global Optimization, Springer, vol. 90(4), pages 843-868, December.
  15. Li, Jingwang & An, Qing & Su, Housheng, 2023. "Proximal nested primal-dual gradient algorithms for distributed constraint-coupled composite optimization," Applied Mathematics and Computation, Elsevier, vol. 444(C).
  16. 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.
  17. Shariat Torbaghan, Shahab & Madani, Mehdi & Sels, Peter & Virag, Ana & Le Cadre, Hélène & Kessels, Kris & Mou, Yuting, 2021. "Designing day-ahead multi-carrier markets for flexibility: Models and clearing algorithms," Applied Energy, Elsevier, vol. 285(C).
  18. Shang, Jun & Ye, Haishan & Chang, Xiangyu, 2024. "Accelerated Double-Sketching Subspace Newton," European Journal of Operational Research, Elsevier, vol. 319(2), pages 484-493.
  19. Doikov, Nikita & Nesterov, Yurii, 2021. "Optimization Methods for Fully Composite Problems," LIDAM Discussion Papers CORE 2021001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  20. David Muller & Yurii Nesterov & Vladimir Shikhman, 2021. "Dynamic pricing under nested logit demand," Papers 2101.04486, arXiv.org.
  21. Ramon de Punder & Timo Dimitriadis & Rutger-Jan Lange, 2024. "Kullback-Leibler-based characterizations of score-driven updates," Papers 2408.02391, arXiv.org, revised Sep 2024.
  22. Hailing Wang & Changjun Yu & Yongcun Song, 2024. "An Augmented Lagrangian Method for State Constrained Linear Parabolic Optimal Control Problems," Journal of Optimization Theory and Applications, Springer, vol. 203(1), pages 196-226, October.
  23. Forneron, Jean-Jacques, 2024. "Detecting identification failure in moment condition models," Journal of Econometrics, Elsevier, vol. 238(1).
  24. Wu, Zhengtian & Jiang, Baoping & Karimi, Hamid Reza, 2020. "A logarithmic descent direction algorithm for the quadratic knapsack problem," Applied Mathematics and Computation, Elsevier, vol. 369(C).
  25. Anastasiya Ivanova & Pavel Dvurechensky & Evgeniya Vorontsova & Dmitry Pasechnyuk & Alexander Gasnikov & Darina Dvinskikh & Alexander Tyurin, 2022. "Oracle Complexity Separation in Convex Optimization," Journal of Optimization Theory and Applications, Springer, vol. 193(1), pages 462-490, June.
  26. Paul R. Rosenbaum, 2023. "Sensitivity analyses informed by tests for bias in observational studies," Biometrics, The International Biometric Society, vol. 79(1), pages 475-487, March.
  27. 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.
  28. Lien T. Nguyen & Andrew Eberhard & Xinghuo Yu & Alexander Y. Kruger & Chaojie Li, 2024. "Finite-Time Nonconvex Optimization Using Time-Varying Dynamical Systems," Journal of Optimization Theory and Applications, Springer, vol. 203(1), pages 844-879, October.
  29. Hadi Abbaszadehpeivasti & Etienne Klerk & Moslem Zamani, 2024. "On the Rate of Convergence of the Difference-of-Convex Algorithm (DCA)," Journal of Optimization Theory and Applications, Springer, vol. 202(1), pages 475-496, July.
  30. Xue Gao & Xingju Cai & Deren Han, 2020. "A Gauss–Seidel type inertial proximal alternating linearized minimization for a class of nonconvex optimization problems," Journal of Global Optimization, Springer, vol. 76(4), pages 863-887, April.
  31. Alexander Kononov & Yulia Zakharova, 2022. "Speed scaling scheduling of multiprocessor jobs with energy constraint and makespan criterion," Journal of Global Optimization, Springer, vol. 83(3), pages 539-564, July.
  32. Jean-Jacques Forneron, 2023. "Noisy, Non-Smooth, Non-Convex Estimation of Moment Condition Models," Papers 2301.07196, arXiv.org, revised Feb 2023.
  33. Pham Duy Khanh & Boris S. Mordukhovich & Vo Thanh Phat & Dat Ba Tran, 2023. "Generalized damped Newton algorithms in nonsmooth optimization via second-order subdifferentials," Journal of Global Optimization, Springer, vol. 86(1), pages 93-122, May.
  34. Xin Jiang & Lieven Vandenberghe, 2023. "Bregman Three-Operator Splitting Methods," Journal of Optimization Theory and Applications, Springer, vol. 196(3), pages 936-972, March.
  35. Ziyuan Wang & Andreas Themelis & Hongjia Ou & Xianfu Wang, 2024. "A Mirror Inertial Forward–Reflected–Backward Splitting: Convergence Analysis Beyond Convexity and Lipschitz Smoothness," Journal of Optimization Theory and Applications, Springer, vol. 203(2), pages 1127-1159, November.
  36. Azimbek Khudoyberdiev & Shabir Ahmad & Israr Ullah & DoHyeun Kim, 2020. "An Optimization Scheme Based on Fuzzy Logic Control for Efficient Energy Consumption in Hydroponics Environment," Energies, MDPI, vol. 13(2), pages 1-27, January.
  37. Faybusovich, Leonid & Zhou, Cunlu, 2020. "Self-concordance and matrix monotonicity with applications to quantum entanglement problems," Applied Mathematics and Computation, Elsevier, vol. 375(C).
  38. Whiteley, Nick, 2021. "Dimension-free Wasserstein contraction of nonlinear filters," Stochastic Processes and their Applications, Elsevier, vol. 135(C), pages 31-50.
  39. Huiyi Cao & Kamil A. Khan, 2023. "General convex relaxations of implicit functions and inverse functions," Journal of Global Optimization, Springer, vol. 86(3), pages 545-572, July.
  40. Chung-En Tsai & Hao-Chung Cheng & Yen-Huan Li, 2022. "Online Self-Concordant and Relatively Smooth Minimization, With Applications to Online Portfolio Selection and Learning Quantum States," Papers 2210.00997, arXiv.org, revised Sep 2023.
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