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Broad Learning System Based on Maximum Correntropy Criterion 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 7, 页码: 3083-3097
作者:  Zheng, Yunfei;  Chen, Badong;  Wang, Shiyuan;  Wang, Weiqun
收藏  |  浏览/下载：176/0  |  提交时间：2021/08/15
Learning systems  Robustness  Standards  Optimization  Training  Perturbation methods  Mean square error methods  Broad learning system (BLS)  incremental learning algorithms  maximum correntropy criterion (MCC)  regression and classification  
SRSC: Selective, Robust, and Supervised Constrained Feature Representation for Image Classification 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 10, 页码: 4290-4302
作者:  Xie, Guo-Sen;  Zhang, Zheng;  Liu, Li;  Zhu, Fan;  Zhang, Xu-Yao;  Shao, Ling;  Li, Xuelong
收藏  |  浏览/下载：196/0  |  提交时间：2021/01/07
Training  Task analysis  Learning systems  Computational modeling  Optimization  Support vector machines  Principal component analysis  Feature learning  feature selection  least squares  subspace learning  
Modified Gram-Schmidt Method-Based Variable Projection Algorithm for Separable Nonlinear Models 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 8, 页码: 2410-2418
作者:  Chen, Guang-Yong;  Gan, Min;  Ding, Feng;  Chen, C. L. Philip
收藏  |  浏览/下载：233/0  |  提交时间：2019/12/16
Data fitting  modified Gram-Schmidt (MGS)  parameter estimation  separable nonlinear least-squares problem  variable projection (VP)  
Discriminative Feature Selection via Employing Smooth and Robust Hinge Loss 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 3, 页码: 788-802
作者:  Peng, Hanyang;  Liu, Cheng-Lin
收藏  |  浏览/下载：217/0  |  提交时间：2019/07/12
Accelerated proximal gradient (APG)  extended hinge loss (HL)  feature selection  sparsity regularization  
Adaptive Constrained Optimal Control Design for Data-Based Nonlinear Discrete-Time Systems With Critic-Only Structure 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 6, 页码: 2099-2111
作者:  Luo, Biao;  Liu, Derong;  Wu, Huai-Ning
浏览  |  Adobe PDF(1045Kb)  |  收藏  |  浏览/下载：373/114  |  提交时间：2018/10/10
Adaptive Control  Adaptive Dynamic Programming  Constraints  Critic-only  Data-based  Optimal Control  Q-learning  
Supervised Discrete Hashing With Relaxation 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 3, 页码: 608-617
作者:  Gui, Jie;  Liu, Tongliang;  Sun, Zhenan;  Tao, Dacheng;  Tan, Tieniu
收藏  |  浏览/下载：227/0  |  提交时间：2018/03/03
Data-dependent Hashing  Least Squares Regression  Supervised Discrete Hashing (Sdh)  Supervised Discrete Hashing With Relaxation (Sdhr)  
Robust C-Loss Kernel Classifiers 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 3, 页码: 510-522
作者:  Xu, Guibiao;  Hu, Bao-Gang;  Principe, Jose C.
浏览  |  Adobe PDF(3169Kb)  |  收藏  |  浏览/下载：383/155  |  提交时间：2018/01/05
Correntropy  Half-quadratic (Hq) Optimization  Kernel Classifier  Loss Function  
Groupwise Retargeted Least-Squares Regression 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 4, 页码: 1352-1358
作者:  Wang, Lingfeng;  Pan, Chunhong
浏览  |  Adobe PDF(618Kb)  |  收藏  |  浏览/下载：344/120  |  提交时间：2018/01/04
Groupwise  Least-squares Regression (Lsr)  Multicategory Classification  Retargeted Least-squares Regression (Relsr)  
A Fast Algorithm of Convex Hull Vertices Selection for Online Classification 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 4, 页码: 792-806
作者:  Ding, Shuguang;  Nie, Xiangli;  Qiao, Hong;  Zhang, Bo
浏览  |  Adobe PDF(3029Kb)  |  收藏  |  浏览/下载：388/129  |  提交时间：2017/12/30
Convex Hull Decomposition  Kernel  Online Classification  Projection  
Feature Selection Based on Structured Sparsity: A Comprehensive Study 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2017, 卷号: 28, 期号: 7, 页码: 1490-1507
作者:  Gui, Jie;  Sun, Zhenan;  Ji, Shuiwang;  Tao, Dacheng;  Tan, Tieniu
浏览  |  Adobe PDF(3835Kb)  |  收藏  |  浏览/下载：551/268  |  提交时间：2017/09/12
Dimensionality Reduction  Feature Selection  Sparse  Structured Sparsity