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2020 – today
- 2024
[j46]Ruping Huang, Yan Qin, Kejun Liu, Gonglin Yuan
:
Biased stochastic conjugate gradient algorithm with adaptive step size for nonconvex problems. Expert Syst. Appl. 238(Part C): 121556 (2024)- [j45]Gonglin Yuan, Bing Xue, Mengjie Zhang:
An evolutionary neural architecture search method based on performance prediction and weight inheritance. Inf. Sci. 667: 120466 (2024) - [j44]Xiaoliang Wang, Gonglin Yuan:
An accelerated descent CG algorithm with clustering the eigenvalues for large-scale nonconvex unconstrained optimization and its application in image restoration problems. J. Comput. Appl. Math. 437: 115454 (2024) - [j43]Gonglin Yuan, Zhan Wang, Pengyuan Li:
A modified two-parameter scaled Broyden-type algorithm for unconstrained optimization problems. J. Comput. Appl. Math. 448: 115944 (2024) - [j42]Zhou Sheng, Gonglin Yuan:
Convergence and worst-case complexity of adaptive Riemannian trust-region methods for optimization on manifolds. J. Glob. Optim. 89(4): 949-974 (2024) - [j41]Gonglin Yuan, Xiong Zhao, Kejun Liu, Xiaoxuan Chen:
An adaptive projection BFGS method for nonconvex unconstrained optimization problems. Numer. Algorithms 95(4): 1747-1767 (2024) - [j40]Nan Lin, Weifang Gao, Lian Li, Junhui Chen, Zi Liang, Gonglin Yuan, Heyang Sun, Qing Li, Jianhua Chen, Liri Jin, Yan Huang, Xiangqin Zhou, Shaobo Zhang, Peng Hu, Chaoyue Dai, Haibo He, Yisu Dong, Liying Cui, Qiang Lu:
vEpiNet: A multimodal interictal epileptiform discharge detection method based on video and electroencephalogram data. Neural Networks 175: 106319 (2024) - [j39]Chen Ouyang, Chenkaixiang Lu, Xiong Zhao, Ruping Huang, Gonglin Yuan, Yiyan Jiang:
Stochastic three-term conjugate gradient method with variance technique for non-convex learning. Stat. Comput. 34(3): 107 (2024) - [j38]Weiping Yan, Yu Tang, Gonglin Yuan:
Fast Optimization of Charged Particle Dynamics with Damping. SIAM J. Optim. 34(3): 2287-2313 (2024) - [j37]Gonglin Yuan, Bin Wang, Bing Xue, Mengjie Zhang:
Particle Swarm Optimization for Efficiently Evolving Deep Convolutional Neural Networks Using an Autoencoder-Based Encoding Strategy. IEEE Trans. Evol. Comput. 28(5): 1190-1204 (2024) - 2023
- [j36]Xiaoliang Wang, Gonglin Yuan, Liping Pang:
A class of new three-term descent conjugate gradient algorithms for large-scale unconstrained optimization and applications to image restoration problems. Numer. Algorithms 93(3): 949-970 (2023) - [c7]Gonglin Yuan, Bing Xue, Mengjie Zhang:
An Effective One-Shot Neural Architecture Search Method with Supernet Fine-Tuning for Image Classification. GECCO 2023: 615-623 - [i1]Wenjie Liu, Zixian Li, Gonglin Yuan:
Infeasibility of constructing a special orthogonal matrix for the deterministic remote preparation of arbitrary n-qubit state. CoRR abs/2309.14363 (2023) - 2022
- [j35]Gonglin Yuan, Mengxiang Zhang, Yingjie Zhou:
Adaptive scaling damped BFGS method without gradient Lipschitz continuity. Appl. Math. Lett. 124: 107634 (2022) - [j34]Gonglin Yuan, Zhan Wang, Pengyuan Li:
Global convergence of a nonmonotone Broyden family method for nonconvex unconstrained minimization. Comput. Appl. Math. 41(6) (2022) - [j33]Junyu Lu, Gonglin Yuan, Zhan Wang:
A modified Dai-Liao conjugate gradient method for solving unconstrained optimization and image restoration problems. J. Appl. Math. Comput. 68(2): 681-703 (2022) - [j32]Gonglin Yuan, Ailun Jian, Mengxiang Zhang, Jiajia Yu:
A modified HZ conjugate gradient algorithm without gradient Lipschitz continuous condition for non convex functions. J. Appl. Math. Comput. 68(6): 4691-4712 (2022) - [j31]Gonglin Yuan, Heshu Yang, Mengxiang Zhang:
Adaptive three-term PRP algorithms without gradient Lipschitz continuity condition for nonconvex functions. Numer. Algorithms 91(1): 145-160 (2022) - [j30]Gonglin Yuan, Pengyuan Li, Junyu Lu:
The global convergence of the BFGS method with a modified WWP line search for nonconvex functions. Numer. Algorithms 91(1): 353-365 (2022) - [j29]Dan Luo, Yong Li, Junyu Lu, Gonglin Yuan:
A conjugate gradient algorithm based on double parameter scaled Broyden-Fletcher-Goldfarb-Shanno update for optimization problems and image restoration. Neural Comput. Appl. 34(1): 535-553 (2022) - [j28]Wenjie Liu, Zixian Li, Gonglin Yuan:
of constructing a special orthogonal matrix for the deterministic remote preparation of arbitrary n-qubit state. Quantum Inf. Comput. 22(15&16): 1289-1319 (2022) - 2021
- [j27]Gonglin Yuan, Yingjie Zhou, Liping Wang, Qingyuan Yang:
Stochastic Bigger Subspace Algorithms for Nonconvex Stochastic Optimization. IEEE Access 9: 119818-119829 (2021) - [j26]Gonglin Yuan, Junyu Lu, Zhan Wang:
The modified PRP conjugate gradient algorithm under a non-descent line search and its application in the Muskingum model and image restoration problems. Soft Comput. 25(8): 5867-5879 (2021) - [c6]Gonglin Yuan, Bing Xue, Mengjie Zhang:
A Two-Stage Efficient Evolutionary Neural Architecture Search Method for Image Classification. PRICAI (1) 2021: 469-484 - 2020
- [j25]Gonglin Yuan, Xiaoliang Wang, Zhou Sheng:
The Projection Technique for Two Open Problems of Unconstrained Optimization Problems. J. Optim. Theory Appl. 186(2): 590-619 (2020) - [j24]Gonglin Yuan, Xiaoliang Wang, Zhou Sheng:
Family weak conjugate gradient algorithms and their convergence analysis for nonconvex functions. Numer. Algorithms 84(3): 935-956 (2020) - [c5]Gonglin Yuan, Bing Xue, Mengjie Zhang:
A Graph-Based Approach to Automatic Convolutional Neural Network Construction for Image Classification. IVCNZ 2020: 1-6
2010 – 2019
- 2019
- [j23]Gonglin Yuan, Bopeng Wang, Zhou Sheng:
The Hager-Zhang conjugate gradient algorithm for large-scale nonlinear equations. Int. J. Comput. Math. 96(8): 1533-1547 (2019) - [j22]Zhou Sheng, Qin Ni, Gonglin Yuan:
Local convergence analysis of inverse iteration algorithm for computing the H-spectral radius of a nonnegative weakly irreducible tensor. J. Comput. Appl. Math. 357: 26-37 (2019) - [j21]Gonglin Yuan, Zengxin Wei, Yuning Yang:
The global convergence of the Polak-Ribière-Polyak conjugate gradient algorithm under inexact line search for nonconvex functions. J. Comput. Appl. Math. 362: 262-275 (2019) - 2018
- [j20]Zhou Sheng, Gonglin Yuan:
An effective adaptive trust region algorithm for nonsmooth minimization. Comput. Optim. Appl. 71(1): 251-271 (2018) - [j19]Gonglin Yuan, Zhou Sheng, Bopeng Wang, Wujie Hu, Chunnian Li:
The global convergence of a modified BFGS method for nonconvex functions. J. Comput. Appl. Math. 327: 274-294 (2018) - [c4]Gonglin Yuan, Tingting Li:
A Modified Dai-Yuan Conjugate Gradient Algorithm for Large-Scale Optimization Problems. ICCCS (1) 2018: 132-142 - [c3]Xiaoliang Wang, Wujie Hu, Gonglin Yuan:
A Modified Wei-Yao-Liu Conjugate Gradient Algorithm for Two Type Minimization Optimization Models. ICCCS (1) 2018: 143-159 - 2017
- [c2]Gonglin Yuan, Wujie Hu, Zhou Sheng:
A Conjugate Gradient Algorithm with Yuan-Wei-Lu Line Search. ICCCS (2) 2017: 738-746 - 2016
- [j18]Gonglin Yuan, Zehong Meng, Yong Li:
A Modified Hestenes and Stiefel Conjugate Gradient Algorithm for Large-Scale Nonsmooth Minimizations and Nonlinear Equations. J. Optim. Theory Appl. 168(1): 129-152 (2016) - [c1]Gonglin Yuan, Gaohui Peng:
New Conjugate Gradient Algorithms Based on New Conjugacy Condition. ICCCS (2) 2016: 498-509 - 2015
- [j17]Gonglin Yuan, Maojun Zhang:
A three-terms Polak-Ribière-Polyak conjugate gradient algorithm for large-scale nonlinear equations. J. Comput. Appl. Math. 286: 186-195 (2015) - [j16]Gonglin Yuan, Zengxin Wei, Maojun Zhang:
An active-set projected trust region algorithm for box constrained optimization problems. J. Syst. Sci. Complex. 28(5): 1128-1147 (2015) - 2014
- [j15]Gonglin Yuan, Zengxin Wei, Guoyin Li:
A modified Polak-Ribière-Polyak conjugate gradient algorithm for nonsmooth convex programs. J. Comput. Appl. Math. 255: 86-96 (2014) - 2013
- [j14]Gonglin Yuan, Zengxin Wei, Zhongxing Wang:
Gradient trust region algorithm with limited memory BFGS update for nonsmooth convex minimization. Comput. Optim. Appl. 54(1): 45-64 (2013) - 2011
- [j13]Gonglin Yuan, Zengxin Wei, Xiwen Lu:
A BFGS trust-region method for nonlinear equations. Computing 92(4): 317-333 (2011) - [j12]Gonglin Yuan, Sha Lu, Zengxin Wei:
A new trust-region method with line search for solving symmetric nonlinear equations. Int. J. Comput. Math. 88(10): 2109-2123 (2011) - [j11]Gonglin Yuan, Zengxin Wei, Sha Lu:
Limited memory BFGS method with backtracking for symmetric nonlinear equations. Math. Comput. Model. 54(1-2): 367-377 (2011) - 2010
- [j10]Gonglin Yuan, Zengxin Wei:
Convergence analysis of a modified BFGS method on convex minimizations. Comput. Optim. Appl. 47(2): 237-255 (2010) - [j9]Gonglin Yuan, Sha Lu, Zengxin Wei:
A Line Search Algorithm for Unconstrained Optimization. J. Softw. Eng. Appl. 3(5): 503-509 (2010)
2000 – 2009
- 2009
- [j8]Gonglin Yuan, Shide Meng, Zengxin Wei:
A Trust-Region-Based BFGS Method with Line Search Technique for Symmetric Nonlinear Equations. Adv. Oper. Res. 2009: 909753:1-909753:22 (2009) - [j7]Gonglin Yuan, Xiwen Lu:
A modified PRP conjugate gradient method. Ann. Oper. Res. 166(1): 73-90 (2009) - [j6]Gonglin Yuan, Zhongxing Wang, Zengxin Wei:
A Rank-One Fitting Method with Descent Direction for Solving Symmetric Nonlinear Equations. Int. J. Commun. Netw. Syst. Sci. 2(6): 555-561 (2009) - [j5]Gonglin Yuan:
A Conjugate Gradient Method for Unconstrained Optimization Problems. Int. J. Math. Math. Sci. 2009: 329623:1-329623:14 (2009) - [j4]Gonglin Yuan, Xiwen Lu, Zengxin Wei:
A conjugate gradient method with descent direction for unconstrained optimization. J. Comput. Appl. Math. 233(2): 519-530 (2009) - [j3]Gonglin Yuan:
Modified nonlinear conjugate gradient methods with sufficient descent property for large-scale optimization problems. Optim. Lett. 3(1): 11-21 (2009) - 2008
- [j2]Gonglin Yuan, Xiwen Lu:
A new backtracking inexact BFGS method for symmetric nonlinear equations. Comput. Math. Appl. 55(1): 116-129 (2008) - 2004
- [j1]Zengxin Wei, Gaohang Yu, Gonglin Yuan, Zhigang Lian:
The Superlinear Convergence of a Modified BFGS-Type Method for Unconstrained Optimization. Comput. Optim. Appl. 29(3): 315-332 (2004)
Coauthor Index
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