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 *

124 related articles for article (PubMed ID: 10953243)

  • 1. Gradient-based optimization of hyperparameters.
    Bengio Y
    Neural Comput; 2000 Aug; 12(8):1889-900. PubMed ID: 10953243
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Efficient gradient computation for optimization of hyperparameters.
    Xu J; Noo F
    Phys Med Biol; 2022 Feb; 67(3):. PubMed ID: 34920440
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Gradient based hyperparameter optimization in Echo State Networks.
    Thiede LA; Parlitz U
    Neural Netw; 2019 Jul; 115():23-29. PubMed ID: 30921562
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Integrated Evolutionary Learning: An Artificial Intelligence Approach to Joint Learning of Features and Hyperparameters for Optimized, Explainable Machine Learning.
    de Lacy N; Ramshaw MJ; Kutz JN
    Front Artif Intell; 2022; 5():832530. PubMed ID: 35493616
    [TBL] [Abstract][Full Text] [Related]  

  • 5. SVM Modeling via a Hybrid Genetic Strategy. A Health Care Application.
    Cohen G; Hilario M; Pellegrini C; Geissbuhler A
    Stud Health Technol Inform; 2005; 116():193-8. PubMed ID: 16160258
    [TBL] [Abstract][Full Text] [Related]  

  • 6. The Q-norm complexity measure and the minimum gradient method: a novel approach to the machine learning structural risk minimization problem.
    Vieira DA; Takahashi RH; Palade V; Vasconcelos JA; Caminhas WM
    IEEE Trans Neural Netw; 2008 Aug; 19(8):1415-30. PubMed ID: 18701371
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Hyperparameter Optimization Techniques for Designing Software Sensors Based on Artificial Neural Networks.
    Blume S; Benedens T; Schramm D
    Sensors (Basel); 2021 Dec; 21(24):. PubMed ID: 34960528
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Learning the Effect of Registration Hyperparameters with HyperMorph.
    Hoopes A; Hoffmann M; Greve DN; Fischl B; Guttag J; Dalca AV
    J Mach Learn Biomed Imaging; 2022 Mar; 1():. PubMed ID: 36147449
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Optimizing hyperparameters of deep reinforcement learning for autonomous driving based on whale optimization algorithm.
    Ashraf NM; Mostafa RR; Sakr RH; Rashad MZ
    PLoS One; 2021; 16(6):e0252754. PubMed ID: 34111168
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Heuristic hyperparameter optimization of deep learning models for genomic prediction.
    Han J; Gondro C; Reid K; Steibel JP
    G3 (Bethesda); 2021 Jul; 11(7):. PubMed ID: 33993261
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Bayesian approach to feature selection and parameter tuning for support vector machine classifiers.
    Gold C; Holub A; Sollich P
    Neural Netw; 2005; 18(5-6):693-701. PubMed ID: 16111861
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Faster self-organizing fuzzy neural network training and a hyperparameter analysis for a brain-computer interface.
    Coyle D; Prasad G; McGinnity TM
    IEEE Trans Syst Man Cybern B Cybern; 2009 Dec; 39(6):1458-71. PubMed ID: 19493851
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Hyperparameter optimization for image analysis: application to prostate tissue images and live cell data of virus-infected cells.
    Ritter C; Wollmann T; Bernhard P; Gunkel M; Braun DM; Lee JY; Meiners J; Simon R; Sauter G; Erfle H; Rippe K; Bartenschlager R; Rohr K
    Int J Comput Assist Radiol Surg; 2019 Nov; 14(11):1847-1857. PubMed ID: 31177423
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Genetic CFL: Hyperparameter Optimization in Clustered Federated Learning.
    Agrawal S; Sarkar S; Alazab M; Maddikunta PKR; Gadekallu TR; Pham QV
    Comput Intell Neurosci; 2021; 2021():7156420. PubMed ID: 34840562
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Novel maximum-margin training algorithms for supervised neural networks.
    Ludwig O; Nunes U
    IEEE Trans Neural Netw; 2010 Jun; 21(6):972-84. PubMed ID: 20409990
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Lie-group-type neural system learning by manifold retractions.
    Fiori S
    Neural Netw; 2008 Dec; 21(10):1524-9. PubMed ID: 18980831
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Application of Machine Learning to Child Mode Choice with a Novel Technique to Optimize Hyperparameters.
    Naseri H; Waygood EOD; Wang B; Patterson Z
    Int J Environ Res Public Health; 2022 Dec; 19(24):. PubMed ID: 36554720
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Solution path for manifold regularized semisupervised classification.
    Wang G; Wang F; Chen T; Yeung DY; Lochovsky FH
    IEEE Trans Syst Man Cybern B Cybern; 2012 Apr; 42(2):308-19. PubMed ID: 22010154
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Analysis of the distance between two classes for tuning SVM hyperparameters.
    Sun J; Zheng C; Li X; Zhou Y
    IEEE Trans Neural Netw; 2010 Feb; 21(2):305-18. PubMed ID: 20071257
    [TBL] [Abstract][Full Text] [Related]  

  • 20.
    ; ; . PubMed ID:
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 7.