182 related articles for article (PubMed ID: 34634606)
1. The generalized extreme learning machines: Tuning hyperparameters and limiting approach for the Moore-Penrose generalized inverse.
Kim M
Neural Netw; 2021 Dec; 144():591-602. PubMed ID: 34634606
[TBL] [Abstract][Full Text] [Related]
2. Theoretical bounds of generalization error for generalized extreme learning machine and random vector functional link network.
Kim M
Neural Netw; 2023 Jul; 164():49-66. PubMed ID: 37146449
[TBL] [Abstract][Full Text] [Related]
3. Tuning extreme learning machine by an improved electromagnetism-like mechanism algorithm for classification problem.
Zhang MY; Wu Q; Xu ZZ
Math Biosci Eng; 2019 May; 16(5):4692-4707. PubMed ID: 31499684
[TBL] [Abstract][Full Text] [Related]
4. Human-guided auto-labeling for network traffic data: The GELM approach.
Kim M; Lee I
Neural Netw; 2022 Aug; 152():510-526. PubMed ID: 35660547
[TBL] [Abstract][Full Text] [Related]
5. A Hybrid Method Based on Extreme Learning Machine and Self Organizing Map for Pattern Classification.
Jammoussi I; Ben Nasr M
Comput Intell Neurosci; 2020; 2020():2918276. PubMed ID: 32908471
[TBL] [Abstract][Full Text] [Related]
6. Universal approximation of extreme learning machine with adaptive growth of hidden nodes.
Zhang R; Lan Y; Huang GB; Xu ZB
IEEE Trans Neural Netw Learn Syst; 2012 Feb; 23(2):365-71. PubMed ID: 24808516
[TBL] [Abstract][Full Text] [Related]
7. Sparse Bayesian extreme learning machine for multi-classification.
Luo J; Vong CM; Wong PK
IEEE Trans Neural Netw Learn Syst; 2014 Apr; 25(4):836-43. PubMed ID: 24807961
[TBL] [Abstract][Full Text] [Related]
8. Logistic regression paradigm for training a single-hidden layer feedforward neural network. Application to gene expression datasets for cancer research.
Belciug S
J Biomed Inform; 2020 Feb; 102():103373. PubMed ID: 31901506
[TBL] [Abstract][Full Text] [Related]
9. Functional extreme learning machine for regression and classification.
Liu X; Zhou Y; Meng W; Luo Q
Math Biosci Eng; 2023 Jan; 20(2):3768-3792. PubMed ID: 36899604
[TBL] [Abstract][Full Text] [Related]
10. An improvement of extreme learning machine for compact single-hidden-layer feedforward neural networks.
Huynh HT; Won Y; Kim JJ
Int J Neural Syst; 2008 Oct; 18(5):433-41. PubMed ID: 18991365
[TBL] [Abstract][Full Text] [Related]
11. Dynamic adjustment of hidden node parameters for extreme learning machine.
Feng G; Lan Y; Zhang X; Qian Z
IEEE Trans Cybern; 2015 Feb; 45(2):279-88. PubMed ID: 24919208
[TBL] [Abstract][Full Text] [Related]
12. Extreme Learning Machine for Multilayer Perceptron.
Tang J; Deng C; Huang GB
IEEE Trans Neural Netw Learn Syst; 2016 Apr; 27(4):809-21. PubMed ID: 25966483
[TBL] [Abstract][Full Text] [Related]
13. Improving Classification Performance through an Advanced Ensemble Based Heterogeneous Extreme Learning Machines.
Abuassba AOM; Zhang D; Luo X; Shaheryar A; Ali H
Comput Intell Neurosci; 2017; 2017():3405463. PubMed ID: 28546808
[TBL] [Abstract][Full Text] [Related]
14. Error minimized extreme learning machine with growth of hidden nodes and incremental learning.
Feng G; Huang GB; Lin Q; Gay R
IEEE Trans Neural Netw; 2009 Aug; 20(8):1352-7. PubMed ID: 19596632
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. [An Improved ELM Algorithm for Near Infrared Spectral Quantitative Analysis].
Zhang HG; Lu JG
Guang Pu Xue Yu Guang Pu Fen Xi; 2016 Sep; 36(9):2784-8. PubMed ID: 30084595
[TBL] [Abstract][Full Text] [Related]
17. Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine.
Zhao F; Liu Y; Huo K; Zhang S; Zhang Z
Sensors (Basel); 2018 Jan; 18(1):. PubMed ID: 29320453
[TBL] [Abstract][Full Text] [Related]
18. Extreme Learning Machine With Subnetwork Hidden Nodes for Regression and Classification.
Yang Y; Wu QM
IEEE Trans Cybern; 2016 Dec; 46(12):2885-2898. PubMed ID: 26552104
[TBL] [Abstract][Full Text] [Related]
19. Generalized single-hidden layer feedforward networks for regression problems.
Wang N; Er MJ; Han M
IEEE Trans Neural Netw Learn Syst; 2015 Jun; 26(6):1161-76. PubMed ID: 25051564
[TBL] [Abstract][Full Text] [Related]
20. A Fast SVD-Hidden-nodes based Extreme Learning Machine for Large-Scale Data Analytics.
Deng WY; Bai Z; Huang GB; Zheng QH
Neural Netw; 2016 May; 77():14-28. PubMed ID: 26907860
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]