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 *

131 related articles for article (PubMed ID: 18263316)

  • 21. Parametrization of analytic interatomic potential functions using neural networks.
    Malshe M; Narulkar R; Raff LM; Hagan M; Bukkapatnam S; Komanduri R
    J Chem Phys; 2008 Jul; 129(4):044111. PubMed ID: 18681638
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Global Boltzmann perceptron network for online learning of conditional distributions.
    Thathachar ML; Arvind MT
    IEEE Trans Neural Netw; 1999; 10(5):1090-8. PubMed ID: 18252611
    [TBL] [Abstract][Full Text] [Related]  

  • 23. On adaptive learning rate that guarantees convergence in feedforward networks.
    Behera L; Kumar S; Patnaik A
    IEEE Trans Neural Netw; 2006 Sep; 17(5):1116-25. PubMed ID: 17001974
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Stochastic error whitening algorithm for linear filter estimation with noisy data.
    Rao YN; Erdogmus D; Rao GY; Principe JC
    Neural Netw; 2003; 16(5-6):873-80. PubMed ID: 12850046
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Function approximation using fuzzy neural networks with robust learning algorithm.
    Wang WY; Lee TT; Liu CL; Wang CH
    IEEE Trans Syst Man Cybern B Cybern; 1997; 27(4):740-7. PubMed ID: 18255916
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Wavelet-generalized least squares: a new BLU estimator of linear regression models with 1/f errors.
    Fadili MJ; Bullmore ET
    Neuroimage; 2002 Jan; 15(1):217-32. PubMed ID: 11771991
    [TBL] [Abstract][Full Text] [Related]  

  • 27. The layer-wise method and the backpropagation hybrid approach to learning a feedforward neural network.
    Rubanov NS
    IEEE Trans Neural Netw; 2000; 11(2):295-305. PubMed ID: 18249761
    [TBL] [Abstract][Full Text] [Related]  

  • 28. A mean field view of the landscape of two-layer neural networks.
    Mei S; Montanari A; Nguyen PM
    Proc Natl Acad Sci U S A; 2018 Aug; 115(33):E7665-E7671. PubMed ID: 30054315
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Stochastic Training of Neural Networks via Successive Convex Approximations.
    Scardapane S; Di Lorenzo P
    IEEE Trans Neural Netw Learn Syst; 2018 Oct; 29(10):4947-4956. PubMed ID: 29994756
    [TBL] [Abstract][Full Text] [Related]  

  • 30. TAO-robust backpropagation learning algorithm.
    Pernía-Espinoza AV; Ordieres-Meré JB; Martínez-de-Pisón FJ; González-Marcos A
    Neural Netw; 2005 Mar; 18(2):191-204. PubMed ID: 15795116
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Learning algorithms for feedforward networks based on finite samples.
    Rao NV; Protopopescu V; Mann RC; Oblow EM; Iyengar SS
    IEEE Trans Neural Netw; 1996; 7(4):926-40. PubMed ID: 18263488
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Estimations of error bounds for neural-network function approximators.
    Townsend NW; Tarassenko L
    IEEE Trans Neural Netw; 1999; 10(2):217-30. PubMed ID: 18252522
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Multidimensional Gains for Stochastic Approximation.
    Saab SS; Shen D
    IEEE Trans Neural Netw Learn Syst; 2020 May; 31(5):1602-1615. PubMed ID: 31265420
    [TBL] [Abstract][Full Text] [Related]  

  • 34. New learning automata based algorithms for adaptation of backpropagation algorithm parameters.
    Meybodi MR; Beigy H
    Int J Neural Syst; 2002 Feb; 12(1):45-67. PubMed ID: 11852444
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Multiwavelet neural network and its approximation properties.
    Jiao L; Pan J; Fang Y
    IEEE Trans Neural Netw; 2001; 12(5):1060-6. PubMed ID: 18249933
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Parameter incremental learning algorithm for neural networks.
    Wan S; Banta LE
    IEEE Trans Neural Netw; 2006 Nov; 17(6):1424-38. PubMed ID: 17131658
    [TBL] [Abstract][Full Text] [Related]  

  • 37. On the optimality of neural-network approximation using incremental algorithms.
    Meir R; Maiorov VE
    IEEE Trans Neural Netw; 2000; 11(2):323-37. PubMed ID: 18249764
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Comparative study of stochastic algorithms for system optimization based on gradient approximations.
    Chin DC
    IEEE Trans Syst Man Cybern B Cybern; 1997; 27(2):244-9. PubMed ID: 18255862
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Using random weights to train multilayer networks of hard-limiting units.
    Barlett PL; Downs T
    IEEE Trans Neural Netw; 1992; 3(2):202-10. PubMed ID: 18276421
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Analysis of convergence performance of neural networks ranking algorithm.
    Zhang Y; Cao F
    Neural Netw; 2012 Oct; 34():65-71. PubMed ID: 22853999
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.