166 related articles for article (PubMed ID: 30281509)
1. Automatic Tuning of the RBF Kernel Parameter for Batch-Mode Active Learning Algorithms: A Scalable Framework.
Chang CC; Huang HT
IEEE Trans Cybern; 2019 Dec; 49(12):4460-4472. PubMed ID: 30281509
[TBL] [Abstract][Full Text] [Related]
2. Data classification with radial basis function networks based on a novel kernel density estimation algorithm.
Oyang YJ; Hwang SC; Ou YY; Chen CY; Chen ZW
IEEE Trans Neural Netw; 2005 Jan; 16(1):225-36. PubMed ID: 15732402
[TBL] [Abstract][Full Text] [Related]
3. Prototype Regularized Manifold Regularization Technique for Semi-Supervised Online Extreme Learning Machine.
Muhammad Zaly Shah MZ; Zainal A; Ghaleb FA; Al-Qarafi A; Saeed F
Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35590801
[TBL] [Abstract][Full Text] [Related]
4. Best harmony, unified RPCL and automated model selection for unsupervised and supervised learning on Gaussian mixtures, three-layer nets and ME-RBF-SVM models.
Xu L
Int J Neural Syst; 2001 Feb; 11(1):43-69. PubMed ID: 11310554
[TBL] [Abstract][Full Text] [Related]
5. Cost-Effective Object Detection: Active Sample Mining With Switchable Selection Criteria.
Wang K; Lin L; Yan X; Chen Z; Zhang D; Zhang L
IEEE Trans Neural Netw Learn Syst; 2019 Mar; 30(3):834-850. PubMed ID: 30059324
[TBL] [Abstract][Full Text] [Related]
6. Vigilance estimation using truncated l1 distance kernel-based sparse representation regression with physiological signals.
Zhang X; Wang D; Wu H; Chao J; Zhong J; Peng H; Hu B
Comput Methods Programs Biomed; 2023 Dec; 242():107773. PubMed ID: 37734218
[TBL] [Abstract][Full Text] [Related]
7. Batch Mode Active Sampling based on Marginal Probability Distribution Matching.
Chattopadhyay R; Wang Z; Fan W; Davidson I; Panchanathan S; Ye J
KDD; 2012; 2012():741-749. PubMed ID: 25309807
[TBL] [Abstract][Full Text] [Related]
8. A kernel-induced space selection approach to model selection in KLDA.
Wang L; Chan KL; Xue P; Zhou L
IEEE Trans Neural Netw; 2008 Dec; 19(12):2116-31. PubMed ID: 19054735
[TBL] [Abstract][Full Text] [Related]
9. Back to the Future: Radial Basis Function Network Revisited.
Que Q; Belkin M
IEEE Trans Pattern Anal Mach Intell; 2020 Aug; 42(8):1856-1867. PubMed ID: 30908191
[TBL] [Abstract][Full Text] [Related]
10. Design of a multiple kernel learning algorithm for LS-SVM by convex programming.
Jian L; Xia Z; Liang X; Gao C
Neural Netw; 2011 Jun; 24(5):476-83. PubMed ID: 21441012
[TBL] [Abstract][Full Text] [Related]
11. A multi-label learning based kernel automatic recommendation method for support vector machine.
Zhang X; Song Q
PLoS One; 2015; 10(3):e0120455. PubMed ID: 25893896
[TBL] [Abstract][Full Text] [Related]
12. Adaptive Batch Mode Active Learning.
Chakraborty S; Balasubramanian V; Panchanathan S
IEEE Trans Neural Netw Learn Syst; 2015 Aug; 26(8):1747-60. PubMed ID: 25291799
[TBL] [Abstract][Full Text] [Related]
13. Soft margin multiple kernel learning.
Xu X; Tsang IW; Xu D
IEEE Trans Neural Netw Learn Syst; 2013 May; 24(5):749-61. PubMed ID: 24808425
[TBL] [Abstract][Full Text] [Related]
14. Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels.
Jayasumana S; Hartley R; Salzmann M; Li H; Harandi M
IEEE Trans Pattern Anal Mach Intell; 2015 Dec; 37(12):2464-77. PubMed ID: 26539851
[TBL] [Abstract][Full Text] [Related]
15. Active learning for solving the incomplete data problem in facial age classification by the furthest nearest-neighbor criterion.
Wang JG; Sung E; Yau WY
IEEE Trans Image Process; 2011 Jul; 20(7):2049-62. PubMed ID: 21245008
[TBL] [Abstract][Full Text] [Related]
16. Variable selection in nonlinear modeling based on RBF networks and evolutionary computation.
Patrinos P; Alexandridis A; Ninos K; Sarimveis H
Int J Neural Syst; 2010 Oct; 20(5):365-79. PubMed ID: 20945516
[TBL] [Abstract][Full Text] [Related]
17. A framework for parameter estimation and model selection in kernel deep stacking networks.
Welchowski T; Schmid M
Artif Intell Med; 2016 Jun; 70():31-40. PubMed ID: 27431035
[TBL] [Abstract][Full Text] [Related]
18. Sparse multiple kernel learning for signal processing applications.
Subrahmanya N; Shin YC
IEEE Trans Pattern Anal Mach Intell; 2010 May; 32(5):788-98. PubMed ID: 20299705
[TBL] [Abstract][Full Text] [Related]
19. Online selective kernel-based temporal difference learning.
Chen X; Gao Y; Wang R
IEEE Trans Neural Netw Learn Syst; 2013 Dec; 24(12):1944-56. PubMed ID: 24805214
[TBL] [Abstract][Full Text] [Related]
20. Kernel Path for Semisupervised Support Vector Machine.
Zhai Z; Huang H; Gu B
IEEE Trans Neural Netw Learn Syst; 2024 Feb; 35(2):1512-1522. PubMed ID: 35731767
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
