IDEAS home Printed from https://ideas.repec.org/r/spr/spochp/978-1-4419-9569-8_10.html
   My bibliography  Save this item

Proximal Splitting Methods in Signal Processing

In: Fixed-Point Algorithms for Inverse Problems in Science and Engineering

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Rodrigo Verschae & Takekazu Kato & Takashi Matsuyama, 2016. "Energy Management in Prosumer Communities: A Coordinated Approach," Energies, MDPI, vol. 9(7), pages 1-27, July.
  2. Sarah Perrin & Thierry Roncalli, 2019. "Machine Learning Optimization Algorithms & Portfolio Allocation," Papers 1909.10233, arXiv.org.
  3. 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.
  4. Julian Rasch & Antonin Chambolle, 2020. "Inexact first-order primal–dual algorithms," Computational Optimization and Applications, Springer, vol. 76(2), pages 381-430, June.
  5. Jérôme Bolte & Edouard Pauwels, 2016. "Majorization-Minimization Procedures and Convergence of SQP Methods for Semi-Algebraic and Tame Programs," Mathematics of Operations Research, INFORMS, vol. 41(2), pages 442-465, May.
  6. Yonghong Yao & Abubakar Adamu & Yekini Shehu, 2024. "Forward–Reflected–Backward Splitting Algorithms with Momentum: Weak, Linear and Strong Convergence Results," Journal of Optimization Theory and Applications, Springer, vol. 201(3), pages 1364-1397, June.
  7. 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.
  8. Guillaume Sagnol & Edouard Pauwels, 2019. "An unexpected connection between Bayes A-optimal designs and the group lasso," Statistical Papers, Springer, vol. 60(2), pages 565-584, April.
  9. Guan Yu & Yufeng Liu, 2016. "Sparse Regression Incorporating Graphical Structure Among Predictors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 707-720, April.
  10. Ernest K. Ryu & Yanli Liu & Wotao Yin, 2019. "Douglas–Rachford splitting and ADMM for pathological convex optimization," Computational Optimization and Applications, Springer, vol. 74(3), pages 747-778, December.
  11. Damek Davis & Wotao Yin, 2017. "Faster Convergence Rates of Relaxed Peaceman-Rachford and ADMM Under Regularity Assumptions," Mathematics of Operations Research, INFORMS, vol. 42(3), pages 783-805, August.
  12. S. Bonettini & M. Prato & S. Rebegoldi, 2023. "A nested primal–dual FISTA-like scheme for composite convex optimization problems," Computational Optimization and Applications, Springer, vol. 84(1), pages 85-123, January.
  13. Junhong Lin & Lorenzo Rosasco & Silvia Villa & Ding-Xuan Zhou, 2018. "Modified Fejér sequences and applications," Computational Optimization and Applications, Springer, vol. 71(1), pages 95-113, September.
  14. 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.
  15. Donghwan Kim & Jeffrey A. Fessler, 2018. "Adaptive Restart of the Optimized Gradient Method for Convex Optimization," Journal of Optimization Theory and Applications, Springer, vol. 178(1), pages 240-263, July.
  16. Na Zhao & Qingzhi Yang & Yajun Liu, 2017. "Computing the generalized eigenvalues of weakly symmetric tensors," Computational Optimization and Applications, Springer, vol. 66(2), pages 285-307, March.
  17. Weiyang Ding & Michael K. Ng & Wenxing Zhang, 2024. "A generalized alternating direction implicit method for consensus optimization: application to distributed sparse logistic regression," Journal of Global Optimization, Springer, vol. 90(3), pages 727-753, November.
  18. Jérôme Bolte & Cyrille W. Combettes & Edouard Pauwels, 2024. "The Iterates of the Frank–Wolfe Algorithm May Not Converge," Mathematics of Operations Research, INFORMS, vol. 49(4), pages 2565-2578, November.
  19. 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.
  20. Zhongming Wu & Min Li, 2019. "General inertial proximal gradient method for a class of nonconvex nonsmooth optimization problems," Computational Optimization and Applications, Springer, vol. 73(1), pages 129-158, May.
  21. Mingyi Hong & Tsung-Hui Chang & Xiangfeng Wang & Meisam Razaviyayn & Shiqian Ma & Zhi-Quan Luo, 2020. "A Block Successive Upper-Bound Minimization Method of Multipliers for Linearly Constrained Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 45(3), pages 833-861, August.
  22. Silvia Bonettini & Peter Ochs & Marco Prato & Simone Rebegoldi, 2023. "An abstract convergence framework with application to inertial inexact forward–backward methods," Computational Optimization and Applications, Springer, vol. 84(2), pages 319-362, March.
  23. Puya Latafat & Panagiotis Patrinos, 2017. "Asymmetric forward–backward–adjoint splitting for solving monotone inclusions involving three operators," Computational Optimization and Applications, Springer, vol. 68(1), pages 57-93, September.
  24. Majela Pentón Machado & Mauricio Romero Sicre, 2023. "A Projective Splitting Method for Monotone Inclusions: Iteration-Complexity and Application to Composite Optimization," Journal of Optimization Theory and Applications, Springer, vol. 198(2), pages 552-587, August.
  25. 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.
  26. Sun, Shilin & Wang, Tianyang & Yang, Hongxing & Chu, Fulei, 2022. "Damage identification of wind turbine blades using an adaptive method for compressive beamforming based on the generalized minimax-concave penalty function," Renewable Energy, Elsevier, vol. 181(C), pages 59-70.
  27. Bằng Công Vũ, 2015. "A Splitting Algorithm for Coupled System of Primal–Dual Monotone Inclusions," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 993-1025, March.
  28. Sedi Bartz & Rubén Campoy & Hung M. Phan, 2022. "An Adaptive Alternating Direction Method of Multipliers," Journal of Optimization Theory and Applications, Springer, vol. 195(3), pages 1019-1055, December.
  29. Alessandro Mirone & Emmanuel Brun & Paola Coan, 2014. "A Dictionary Learning Approach with Overlap for the Low Dose Computed Tomography Reconstruction and Its Vectorial Application to Differential Phase Tomography," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-18, December.
  30. Chih-Sheng Chuang & Hongjin He & Zhiyuan Zhang, 2022. "A unified Douglas–Rachford algorithm for generalized DC programming," Journal of Global Optimization, Springer, vol. 82(2), pages 331-349, February.
  31. S. Bonettini & M. Prato & S. Rebegoldi, 2018. "A block coordinate variable metric linesearch based proximal gradient method," Computational Optimization and Applications, Springer, vol. 71(1), pages 5-52, September.
  32. Perraudin, Nathanaël & Holighaus, Nicki & Søndergaard, Peter L. & Balazs, Peter, 2018. "Designing Gabor windows using convex optimization," Applied Mathematics and Computation, Elsevier, vol. 330(C), pages 266-287.
  33. Hongwei Liu & Ting Wang & Zexian Liu, 2022. "Some modified fast iterative shrinkage thresholding algorithms with a new adaptive non-monotone stepsize strategy for nonsmooth and convex minimization problems," Computational Optimization and Applications, Springer, vol. 83(2), pages 651-691, November.
  34. Kun Deng & Dayu Huang, 2015. "Optimal Kullback–Leibler approximation of Markov chains via nuclear norm regularisation," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(11), pages 2029-2047, August.
  35. B. Abbas & H. Attouch & Benar F. Svaiter, 2014. "Newton-Like Dynamics and Forward-Backward Methods for Structured Monotone Inclusions in Hilbert Spaces," Journal of Optimization Theory and Applications, Springer, vol. 161(2), pages 331-360, May.
  36. Cornelio, Anastasia & Porta, Federica & Prato, Marco, 2015. "A convergent least-squares regularized blind deconvolution approach," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 173-186.
  37. Lorenzo Stella & Andreas Themelis & Panagiotis Patrinos, 2017. "Forward–backward quasi-Newton methods for nonsmooth optimization problems," Computational Optimization and Applications, Springer, vol. 67(3), pages 443-487, July.
  38. Luis M. Briceño-Arias & Giovanni Chierchia & Emilie Chouzenoux & Jean-Christophe Pesquet, 2019. "A random block-coordinate Douglas–Rachford splitting method with low computational complexity for binary logistic regression," Computational Optimization and Applications, Springer, vol. 72(3), pages 707-726, April.
  39. Gui-Hua Lin & Zhen-Ping Yang & Hai-An Yin & Jin Zhang, 2023. "A dual-based stochastic inexact algorithm for a class of stochastic nonsmooth convex composite problems," Computational Optimization and Applications, Springer, vol. 86(2), pages 669-710, November.
  40. David Degras, 2021. "Sparse group fused lasso for model segmentation: a hybrid approach," 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. 15(3), pages 625-671, September.
  41. Chin How Jeffrey Pang, 2019. "Dykstra’s Splitting and an Approximate Proximal Point Algorithm for Minimizing the Sum of Convex Functions," Journal of Optimization Theory and Applications, Springer, vol. 182(3), pages 1019-1049, September.
  42. A. Chambolle & Ch. Dossal, 2015. "On the Convergence of the Iterates of the “Fast Iterative Shrinkage/Thresholding Algorithm”," Journal of Optimization Theory and Applications, Springer, vol. 166(3), pages 968-982, September.
  43. Verschae, Rodrigo & Kawashima, Hiroaki & Kato, Takekazu & Matsuyama, Takashi, 2016. "Coordinated energy management for inter-community imbalance minimization," Renewable Energy, Elsevier, vol. 87(P2), pages 922-935.
  44. Patrick R. Johnstone & Pierre Moulin, 2017. "Local and global convergence of a general inertial proximal splitting scheme for minimizing composite functions," Computational Optimization and Applications, Springer, vol. 67(2), pages 259-292, June.
  45. Bo Wen & Xiaojun Chen & Ting Kei Pong, 2018. "A proximal difference-of-convex algorithm with extrapolation," Computational Optimization and Applications, Springer, vol. 69(2), pages 297-324, March.
  46. Philippe Mahey & Jonas Koko & Arnaud Lenoir, 2017. "Decomposition methods for a spatial model for long-term energy pricing problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 85(1), pages 137-153, February.
  47. Hedy Attouch & Alexandre Cabot & Zaki Chbani & Hassan Riahi, 2018. "Inertial Forward–Backward Algorithms with Perturbations: Application to Tikhonov Regularization," Journal of Optimization Theory and Applications, Springer, vol. 179(1), pages 1-36, October.
  48. Rui Yao & Shlomo Bekhor, 2023. "A general equilibrium model for multi-passenger ridesharing systems with stable matching," Papers 2303.16595, arXiv.org, revised Dec 2023.
  49. Simon Göppel & Jürgen Frikel & Markus Haltmeier, 2024. "Data-Proximal Complementary ℓ 1 -TV Reconstruction for Limited Data Computed Tomography," Mathematics, MDPI, vol. 12(10), pages 1-20, May.
  50. Anda Tang & Pei Quan & Lingfeng Niu & Yong Shi, 2022. "A Survey for Sparse Regularization Based Compression Methods," Annals of Data Science, Springer, vol. 9(4), pages 695-722, August.
  51. Pan, Chenjian & Ling, Chen & He, Hongjin & Qi, Liqun & Xu, Yanwei, 2024. "A low-rank and sparse enhanced Tucker decomposition approach for tensor completion," Applied Mathematics and Computation, Elsevier, vol. 465(C).
  52. Porta, Federica & Loris, Ignace, 2015. "On some steplength approaches for proximal algorithms," Applied Mathematics and Computation, Elsevier, vol. 253(C), pages 345-362.
  53. Pankaj Gautam & Daya Ram Sahu & Avinash Dixit & Tanmoy Som, 2021. "Forward–Backward–Half Forward Dynamical Systems for Monotone Inclusion Problems with Application to v-GNE," Journal of Optimization Theory and Applications, Springer, vol. 190(2), pages 491-523, August.
  54. Panadda Thongpaen & Rattanakorn Wattanataweekul, 2021. "A Fast Fixed-Point Algorithm for Convex Minimization Problems and Its Application in Image Restoration Problems," Mathematics, MDPI, vol. 9(20), pages 1-13, October.
  55. Le, Khuyen T. & Chaux, Caroline & Richard, Frédéric J.P. & Guedj, Eric, 2020. "An adapted linear discriminant analysis with variable selection for the classification in high-dimension, and an application to medical data," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
  56. Chadarat Thongphaen & Warunun Inthakon & Suthep Suantai & Narawadee Phudolsitthiphat, 2022. "Common Attractive Point Results for Two Generalized Nonexpansive Mappings in Uniformly Convex Banach Spaces," Mathematics, MDPI, vol. 10(8), pages 1-18, April.
  57. Goran Banjac & Paul Goulart & Bartolomeo Stellato & Stephen Boyd, 2019. "Infeasibility Detection in the Alternating Direction Method of Multipliers for Convex Optimization," Journal of Optimization Theory and Applications, Springer, vol. 183(2), pages 490-519, November.
  58. Kong, Yun & Qin, Zhaoye & Wang, Tianyang & Han, Qinkai & Chu, Fulei, 2021. "An enhanced sparse representation-based intelligent recognition method for planet bearing fault diagnosis in wind turbines," Renewable Energy, Elsevier, vol. 173(C), pages 987-1004.
  59. 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).
  60. 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.
  61. Bubba, Tatiana A. & Porta, Federica & Zanghirati, Gaetano & Bonettini, Silvia, 2018. "A nonsmooth regularization approach based on shearlets for Poisson noise removal in ROI tomography," Applied Mathematics and Computation, Elsevier, vol. 318(C), pages 131-152.
  62. Warunun Inthakon & Suthep Suantai & Panitarn Sarnmeta & Dawan Chumpungam, 2020. "A New Machine Learning Algorithm Based on Optimization Method for Regression and Classification Problems," Mathematics, MDPI, vol. 8(6), pages 1-17, June.
  63. Ghaderi, Susan & Ahookhosh, Masoud & Arany, Adam & Skupin, Alexander & Patrinos, Panagiotis & Moreau, Yves, 2024. "Smoothing unadjusted Langevin algorithms for nonsmooth composite potential functions," Applied Mathematics and Computation, Elsevier, vol. 464(C).
  64. Christian Grussler & Pontus Giselsson, 2022. "Efficient Proximal Mapping Computation for Low-Rank Inducing Norms," Journal of Optimization Theory and Applications, Springer, vol. 192(1), pages 168-194, January.
  65. Luis Briceño-Arias & Julio Deride & Cristian Vega, 2022. "Random Activations in Primal-Dual Splittings for Monotone Inclusions with a Priori Information," Journal of Optimization Theory and Applications, Springer, vol. 192(1), pages 56-81, January.
  66. Oumaima Benchettou & Abdeslem Hafid Bentbib & Abderrahman Bouhamidi, 2023. "An Accelerated Tensorial Double Proximal Gradient Method for Total Variation Regularization Problem," Journal of Optimization Theory and Applications, Springer, vol. 198(1), pages 111-134, July.
  67. Bonettini, Silvia & Prato, Marco & Rebegoldi, Simone, 2016. "A cyclic block coordinate descent method with generalized gradient projections," Applied Mathematics and Computation, Elsevier, vol. 286(C), pages 288-300.
  68. Nguyen Hieu Thao, 2018. "A convergent relaxation of the Douglas–Rachford algorithm," Computational Optimization and Applications, Springer, vol. 70(3), pages 841-863, July.
  69. 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.
  70. Joshua S. North & Christopher K. Wikle & Erin M. Schliep, 2023. "A Review of Data‐Driven Discovery for Dynamic Systems," International Statistical Review, International Statistical Institute, vol. 91(3), pages 464-492, December.
  71. Suthep Suantai & Kunrada Kankam & Prasit Cholamjiak, 2020. "A Novel Forward-Backward Algorithm for Solving Convex Minimization Problem in Hilbert Spaces," Mathematics, MDPI, vol. 8(1), pages 1-13, January.
  72. Xiangfeng Wang & Junping Zhang & Wenxing Zhang, 2020. "The distance between convex sets with Minkowski sum structure: application to collision detection," Computational Optimization and Applications, Springer, vol. 77(2), pages 465-490, November.
  73. Ollier, Edouard, 2022. "Fast selection of nonlinear mixed effect models using penalized likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
  74. Ignace Loris & Caroline Verhoeven, 2013. "An iterative algorithm for sparse and constrained recovery with applications to divergence-free current reconstructions in magneto-encephalography," Computational Optimization and Applications, Springer, vol. 54(2), pages 399-416, March.
  75. Mishra, Aditya & Müller, Christian L., 2022. "Robust regression with compositional covariates," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).
  76. Xin Jiang & Lieven Vandenberghe, 2023. "Bregman Three-Operator Splitting Methods," Journal of Optimization Theory and Applications, Springer, vol. 196(3), pages 936-972, March.
  77. Minh Pham & Xiaodong Lin & Andrzej Ruszczyński & Yu Du, 2021. "An outer–inner linearization method for non-convex and nondifferentiable composite regularization problems," Journal of Global Optimization, Springer, vol. 81(1), pages 179-202, September.
  78. Wang, Yugang & Huang, Ting-Zhu & Zhao, Xi-Le & Deng, Liang-Jian & Ji, Teng-Yu, 2020. "A convex single image dehazing model via sparse dark channel prior," Applied Mathematics and Computation, Elsevier, vol. 375(C).
  79. Trong Phong Nguyen & Edouard Pauwels & Emile Richard & Bruce W. Suter, 2018. "Extragradient Method in Optimization: Convergence and Complexity," Journal of Optimization Theory and Applications, Springer, vol. 176(1), pages 137-162, January.
  80. Pooja Gupta & Angshul Majumdar & Emilie Chouzenoux & Giovanni Chierchia, 2020. "SuperDeConFuse: A Supervised Deep Convolutional Transform based Fusion Framework for Financial Trading Systems," Papers 2011.04364, arXiv.org.
  81. Ah-Pine, Julien, 2022. "Learning doubly stochastic and nearly idempotent affinity matrix for graph-based clustering," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1069-1078.
  82. Rafael E. Carrillo & Martin Leblanc & Baptiste Schubnel & Renaud Langou & Cyril Topfel & Pierre-Jean Alet, 2020. "High-Resolution PV Forecasting from Imperfect Data: A Graph-Based Solution," Energies, MDPI, vol. 13(21), pages 1-17, November.
  83. Alberto De Marchi & Andreas Themelis, 2022. "Proximal Gradient Algorithms Under Local Lipschitz Gradient Continuity," Journal of Optimization Theory and Applications, Springer, vol. 194(3), pages 771-794, September.
  84. Brendan O’Donoghue & Eric Chu & Neal Parikh & Stephen Boyd, 2016. "Conic Optimization via Operator Splitting and Homogeneous Self-Dual Embedding," Journal of Optimization Theory and Applications, Springer, vol. 169(3), pages 1042-1068, June.
  85. Jean-Charles Richard & Thierry Roncalli, 2019. "Constrained Risk Budgeting Portfolios: Theory, Algorithms, Applications & Puzzles," Papers 1902.05710, arXiv.org.
  86. Quoc Tran-Dinh, 2017. "Adaptive smoothing algorithms for nonsmooth composite convex minimization," Computational Optimization and Applications, Springer, vol. 66(3), pages 425-451, April.
  87. Patrick R. Johnstone & Jonathan Eckstein, 2021. "Single-forward-step projective splitting: exploiting cocoercivity," Computational Optimization and Applications, Springer, vol. 78(1), pages 125-166, January.
  88. Yao, Rui & Bekhor, Shlomo, 2023. "A general equilibrium model for multi-passenger ridesharing systems with stable matching," Transportation Research Part B: Methodological, Elsevier, vol. 175(C).
  89. Koplin, Eric & Forzani, Liliana & Tomassi, Diego & Pfeiffer, Ruth M., 2024. "Sufficient dimension reduction for a novel class of zero-inflated graphical models," Computational Statistics & Data Analysis, Elsevier, vol. 196(C).
  90. Heinz H. Bauschke & Valentin R. Koch & Hung M. Phan, 2016. "Stadium Norm and Douglas-Rachford Splitting: A New Approach to Road Design Optimization," Operations Research, INFORMS, vol. 64(1), pages 201-218, February.
  91. Sandy Bitterlich & Radu Ioan Boţ & Ernö Robert Csetnek & Gert Wanka, 2019. "The Proximal Alternating Minimization Algorithm for Two-Block Separable Convex Optimization Problems with Linear Constraints," Journal of Optimization Theory and Applications, Springer, vol. 182(1), pages 110-132, July.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.