BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

341 related articles for article (PubMed ID: 24807446)

  • 1. Function approximation using combined unsupervised and supervised learning.
    Andras P
    IEEE Trans Neural Netw Learn Syst; 2014 Mar; 25(3):495-505. PubMed ID: 24807446
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Bayesian supervised dimensionality reduction.
    Gönen M
    IEEE Trans Cybern; 2013 Dec; 43(6):2179-89. PubMed ID: 23757527
    [TBL] [Abstract][Full Text] [Related]  

  • 3. High-Dimensional Function Approximation With Neural Networks for Large Volumes of Data.
    Andras P
    IEEE Trans Neural Netw Learn Syst; 2018 Feb; 29(2):500-508. PubMed ID: 28129193
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Dimensional reduction for reward-based learning.
    Swinehart CD; Abbott LF
    Network; 2006 Sep; 17(3):235-52. PubMed ID: 17162613
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Dynamic extreme learning machine and its approximation capability.
    Zhang R; Lan Y; Huang GB; Xu ZB; Soh YC
    IEEE Trans Cybern; 2013 Dec; 43(6):2054-65. PubMed ID: 23757515
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Ideal observer approximation using Bayesian classification neural networks.
    Kupinski MA; Edwards DC; Giger ML; Metz CE
    IEEE Trans Med Imaging; 2001 Sep; 20(9):886-99. PubMed ID: 11585206
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Learning-regulated context relevant topographical map.
    Hartono P; Hollensen P; Trappenberg T
    IEEE Trans Neural Netw Learn Syst; 2015 Oct; 26(10):2323-35. PubMed ID: 25546864
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Probability density function learning by unsupervised neurons.
    Fiori S
    Int J Neural Syst; 2001 Oct; 11(5):399-417. PubMed ID: 11709808
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Multilayer in-place learning networks for modeling functional layers in the laminar cortex.
    Weng J; Luwang T; Lu H; Xue X
    Neural Netw; 2008; 21(2-3):150-9. PubMed ID: 18314307
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A new Jacobian matrix for optimal learning of single-layer neural networks.
    Peng JX; Li K; Irwin GW
    IEEE Trans Neural Netw; 2008 Jan; 19(1):119-29. PubMed ID: 18269943
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A growing and pruning sequential learning algorithm of hyper basis function neural network for function approximation.
    Vuković N; Miljković Z
    Neural Netw; 2013 Oct; 46():210-26. PubMed ID: 23811384
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Regularized variational Bayesian learning of echo state networks with delay&sum readout.
    Shutin D; Zechner C; Kulkarni SR; Poor HV
    Neural Comput; 2012 Apr; 24(4):967-95. PubMed ID: 22168555
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparing error minimized extreme learning machines and support vector sequential feed-forward neural networks.
    Romero E; Alquézar R
    Neural Netw; 2012 Jan; 25(1):122-9. PubMed ID: 21959130
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Some comparisons of complexity in dictionary-based and linear computational models.
    Gnecco G; Kůrková V; Sanguineti M
    Neural Netw; 2011 Mar; 24(2):171-82. PubMed ID: 21094023
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Growing hierarchical tree SOM: an unsupervised neural network with dynamic topology.
    Forti A; Foresti GL
    Neural Netw; 2006 Dec; 19(10):1568-80. PubMed ID: 16829025
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Supervised Gaussian process latent variable model for dimensionality reduction.
    Gao X; Wang X; Tao D; Li X
    IEEE Trans Syst Man Cybern B Cybern; 2011 Apr; 41(2):425-34. PubMed ID: 20699213
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A meta-cognitive learning algorithm for a Fully Complex-valued Relaxation Network.
    Savitha R; Suresh S; Sundararajan N
    Neural Netw; 2012 Aug; 32():209-18. PubMed ID: 22386600
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Supervised learning through neuronal response modulation.
    Swinehart CD; Abbott LF
    Neural Comput; 2005 Mar; 17(3):609-31. PubMed ID: 15802008
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Learning algorithms based on linearization.
    Hahnloser R
    Network; 1998 Aug; 9(3):363-80. PubMed ID: 9861996
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Acquisition of nonlinear forward optics in generative models: two-stage "downside-up" learning for occluded vision.
    Tajima S; Watanabe M
    Neural Netw; 2011 Mar; 24(2):148-58. PubMed ID: 21094592
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 18.