These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

147 related articles for article (PubMed ID: 37348433)

  • 1. Two-timescale recurrent neural networks for distributed minimax optimization.
    Xia Z; Liu Y; Wang J; Wang J
    Neural Netw; 2023 Aug; 165():527-539. PubMed ID: 37348433
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A one-layer recurrent neural network for nonsmooth pseudoconvex optimization with quasiconvex inequality and affine equality constraints.
    Liu N; Wang J; Qin S
    Neural Netw; 2022 Mar; 147():1-9. PubMed ID: 34953297
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A two-layer recurrent neural network for nonsmooth convex optimization problems.
    Qin S; Xue X
    IEEE Trans Neural Netw Learn Syst; 2015 Jun; 26(6):1149-60. PubMed ID: 25051563
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A neurodynamic approach to nonlinear optimization problems with affine equality and convex inequality constraints.
    Liu N; Qin S
    Neural Netw; 2019 Jan; 109():147-158. PubMed ID: 30419480
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A collaborative neurodynamic approach with two-timescale projection neural networks designed via majorization-minimization for global optimization and distributed global optimization.
    Li Y; Xia Z; Liu Y; Wang J
    Neural Netw; 2024 Nov; 179():106525. PubMed ID: 39042949
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A second-order accelerated neurodynamic approach for distributed convex optimization.
    Jiang X; Qin S; Xue X; Liu X
    Neural Netw; 2022 Feb; 146():161-173. PubMed ID: 34864224
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A Two-Timescale Duplex Neurodynamic Approach to Mixed-Integer Optimization.
    Che H; Wang J
    IEEE Trans Neural Netw Learn Syst; 2021 Jan; 32(1):36-48. PubMed ID: 32149698
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Cardinality-constrained portfolio selection via two-timescale duplex neurodynamic optimization.
    Leung MF; Wang J; Che H
    Neural Netw; 2022 Sep; 153():399-410. PubMed ID: 35797801
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Projection Neural Network for Constrained Quadratic Minimax Optimization.
    Liu Q; Wang J
    IEEE Trans Neural Netw Learn Syst; 2015 Nov; 26(11):2891-900. PubMed ID: 25966485
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Two-Timescale Multilayer Recurrent Neural Networks for Nonlinear Programming.
    Wang J; Wang J
    IEEE Trans Neural Netw Learn Syst; 2022 Jan; 33(1):37-47. PubMed ID: 33108292
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Minimax and Biobjective Portfolio Selection Based on Collaborative Neurodynamic Optimization.
    Leung MF; Wang J
    IEEE Trans Neural Netw Learn Syst; 2021 Jul; 32(7):2825-2836. PubMed ID: 31902773
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Two-timescale projection neural networks in collaborative neurodynamic approaches to global optimization and distributed optimization.
    Huang B; Liu Y; Jiang YL; Wang J
    Neural Netw; 2024 Jan; 169():83-91. PubMed ID: 37864998
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A novel recurrent neural network for solving nonlinear optimization problems with inequality constraints.
    Xia Y; Feng G; Wang J
    IEEE Trans Neural Netw; 2008 Aug; 19(8):1340-53. PubMed ID: 18701366
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization.
    Liu Q; Guo Z; Wang J
    Neural Netw; 2012 Feb; 26():99-109. PubMed ID: 22019190
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A Two-Timescale Duplex Neurodynamic Approach to Biconvex Optimization.
    Che H; Wang J
    IEEE Trans Neural Netw Learn Syst; 2019 Aug; 30(8):2503-2514. PubMed ID: 30602424
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Collaborative neurodynamic optimization for solving nonlinear equations.
    Guan H; Liu Y; Kou KI; Cao J; Rutkowski L
    Neural Netw; 2023 Aug; 165():483-490. PubMed ID: 37336033
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Design of recurrent neural networks for solving constrained least absolute deviation problems.
    Hu X; Sun C; Zhang B
    IEEE Trans Neural Netw; 2010 Jul; 21(7):1073-86. PubMed ID: 20562048
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A Collective Neurodynamic Approach to Distributed Constrained Optimization.
    Liu Q; Yang S; Wang J
    IEEE Trans Neural Netw Learn Syst; 2017 Aug; 28(8):1747-1758. PubMed ID: 27101621
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A neurodynamic approach to convex optimization problems with general constraint.
    Qin S; Liu Y; Xue X; Wang F
    Neural Netw; 2016 Dec; 84():113-124. PubMed ID: 27718390
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A collective neurodynamic optimization approach to bound-constrained nonconvex optimization.
    Yan Z; Wang J; Li G
    Neural Netw; 2014 Jul; 55():20-9. PubMed ID: 24705545
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.