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Publication search results
found 95 matches
- 2024
- Shummin Nakayama, Yasushi Narushima, Hiroshi Yabe:
Inexact proximal DC Newton-type method for nonconvex composite functions. Comput. Optim. Appl. 87(2): 611-640 (2024) - Honglin Luo, Xianfu Wang, Xinmin Yang:
Various Notions of Nonexpansiveness Coincide for Proximal Mappings of Functions. SIAM J. Optim. 34(1): 642-653 (2024) - Liang Ran, Huaqing Li, Jinhui Hu, Qingguo Lü, Zheng Wang, Zhe Li, Guo Chen:
Distributed Primal-Dual Proximal Algorithms for Convex Optimization Involving Three Composite Functions. IEEE Trans. Control. Netw. Syst. 11(1): 389-401 (2024) - Wei Yao, Chengming Yu, Shangzhi Zeng, Jin Zhang:
Constrained Bi-Level Optimization: Proximal Lagrangian Value function Approach and Hessian-free Algorithm. CoRR abs/2401.16164 (2024) - 2023
- Zohre Aminifard, Saman Babaie-Kafaki:
A diagonally scaled Newton-type proximal method for minimization of the models with nonsmooth composite cost functions. Comput. Appl. Math. 42(8): 353 (2023) - Guiliang Xie, Wei Zhang, Zhi Hu, Gaojian Li:
Upper confident bound advantage function proximal policy optimization. Clust. Comput. 26(3): 2001-2010 (2023) - Julien Hautot, Céline Teulière, Nourddine Azzaoui:
Solving Partially Observable 3D-Visual Tasks with Visual Radial Basis Function Network and Proximal Policy Optimization. Mach. Learn. Knowl. Extr. 5(4): 1888-1904 (2023) - Robert J. Baraldi, Drew P. Kouri:
A proximal trust-region method for nonsmooth optimization with inexact function and gradient evaluations. Math. Program. 201(1): 559-598 (2023) - Zohre Aminifard, Saman Babaie-Kafaki:
An approximate Newton-type proximal method using symmetric rank-one updating formula for minimizing the nonsmooth composite functions. Optim. Methods Softw. 38(3): 529-542 (2023) - Weiwei Kong, Jefferson G. Melo, Renato D. C. Monteiro:
Iteration Complexity of an Inner Accelerated Inexact Proximal Augmented Lagrangian Method Based on the Classical Lagrangian Function. SIAM J. Optim. 33(1): 181-210 (2023) - Tao Zhang, Changqiao Xu, Bingchi Zhang, Xinran Li, Xiaohui Kuang, Luigi Alfredo Grieco:
Towards Attack-Resistant Service Function Chain Migration: A Model-Based Adaptive Proximal Policy Optimization Approach. IEEE Trans. Dependable Secur. Comput. 20(6): 4913-4927 (2023) - Ewa M. Bednarczuk, Giovanni Bruccola, Gabriele Scrivanti, The Hung Tran:
Calculus rules for proximal ε-subdifferentials and inexact proximity operators for weakly convex functions. ECC 2023: 1-8 - Yulan Liu, Yuyang Zhou, Rongrong Lin:
The Proximal Operator of the Piece-wise Exponential Function and Its Application in Compressed Sensing. CoRR abs/2306.13425 (2023) - Feng-Yi Liao, Lijun Ding, Yang Zheng:
Error bounds, PL condition, and quadratic growth for weakly convex functions, and linear convergences of proximal point methods. CoRR abs/2312.16775 (2023) - 2022
- Damek Davis, Dmitriy Drusvyatskiy:
Proximal Methods Avoid Active Strict Saddles of Weakly Convex Functions. Found. Comput. Math. 22(2): 561-606 (2022) - Mahesh Chandra Mukkamala, Jalal Fadili, Peter Ochs:
Global convergence of model function based Bregman proximal minimization algorithms. J. Glob. Optim. 83(4): 753-781 (2022) - Felipe Lara:
On Strongly Quasiconvex Functions: Existence Results and Proximal Point Algorithms. J. Optim. Theory Appl. 192(3): 891-911 (2022) - Morteza Maleknia, Mostafa Shamsi:
A quasi-Newton proximal bundle method using gradient sampling technique for minimizing nonsmooth convex functions. Optim. Methods Softw. 37(4): 1415-1446 (2022) - Zhenran Kuai, Tianyu Wang, Shaowei Wang:
Fair Virtual Network Function Mapping and Scheduling Using Proximal Policy Optimization. IEEE Trans. Commun. 70(11): 7434-7445 (2022) - AmirEmad Ghassami, Andrew Ying, Ilya Shpitser, Eric Tchetgen Tchetgen:
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference. AISTATS 2022: 7210-7239 - Peng Sun, Hai Lin, Huailong Yu, You Zhong, Xiaoping Wu, Bing Sun:
Research on Service Function Chain Deployment Algorithm Based on Proximal Policy Optimization. EITCE 2022: 1920-1925 - Mohamad Albilani, Amel Bouzeghoub:
Dynamic Adjustment of Reward Function for Proximal Policy Optimization with Imitation Learning: Application to Automated Parking Systems. IV 2022: 1400-1408 - Ewa M. Bednarczuk, Giovanni Bruccola, Gabriele Scrivanti, The Hung Tran:
Calculus rules for proximal ε-subdifferentials and inexact proximity operators for weakly convex functions. CoRR abs/2211.14525 (2022) - 2021
- Christian Kanzow, Theresa Lechner:
Globalized inexact proximal Newton-type methods for nonconvex composite functions. Comput. Optim. Appl. 78(2): 377-410 (2021) - Christian Kanzow, Theresa Lechner:
Correction to: Globalized inexact proximal Newton-type methods for nonconvex composite functions. Comput. Optim. Appl. 80(2): 679-680 (2021) - Shummin Nakayama, Yasushi Narushima, Hiroshi Yabe:
Inexact proximal memoryless quasi-Newton methods based on the Broyden family for minimizing composite functions. Comput. Optim. Appl. 79(1): 127-154 (2021) - Patrick L. Combettes, Zev Woodstock:
Reconstruction of functions from prescribed proximal points. J. Approx. Theory 268: 105606 (2021) - Yuanyuan Chen, Zhixia Yang:
Generalized Eigenvalue Proximal Support Vector Machine for Functional Data Classification. Symmetry 13(5): 833 (2021) - Minhui Huang:
Escaping Saddle Points for Nonsmooth Weakly Convex Functions via Perturbed Proximal Algorithms. CoRR abs/2102.02837 (2021) - 2020
- João Xavier da Cruz Neto, Paolo Roberto Oliveira, Antoine Soubeyran, João Carlos de Oliveira Souza:
A generalized proximal linearized algorithm for DC functions with application to the optimal size of the firm problem. Ann. Oper. Res. 289(2): 313-339 (2020)
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