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Stacked BNAS: Rethinking Broad Convolutional Neural Network for Neural Architecture Search 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 0, 期号: 0, 页码: 0
作者:  Zixiang, Ding;  Yaran, Chen;  Nannan, Li;  Dongbin, Zhao;  C.L.Philip Chen,
Adobe PDF(764Kb)  |  收藏  |  浏览/下载：180/28  |  提交时间：2022/01/07
broad neural architecture search, stacked broad convolutional neural network, knowledge embedding search, image classification.  
Dynamic Collaborative Tracking 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 10, 页码: 3035-3046
作者:  Zhu, Guibo;  Zhang, Zhaoxiang;  Wang, Jinqiao;  Wu, Yi;  Lu, Hanqing
浏览  |  Adobe PDF(2492Kb)  |  收藏  |  浏览/下载：466/144  |  提交时间：2018/10/11
Correlation filter (CF)  distracter suppression  online learning  visual tracking  
Manifold Warp Segmentation of Human Action 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 5, 页码: 1414-1426
作者:  Liu, Shenglan;  Feng, Lin;  Liu, Yang;  Qiao, Hong;  Wu, Jun;  Wang, Wei
浏览  |  Adobe PDF(3667Kb)  |  收藏  |  浏览/下载：378/125  |  提交时间：2018/01/06
Curvature  Dimensionality Reduction  Human Action Segmentation  Space Alignment  
In Defense of Locality-Sensitive Hashing 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 1, 页码: 87-103
作者:  Ding, Kun;  Huo, Chunlei;  Fan, Bin;  Xiang, Shiming;  Pan, Chunhong;  Fan B(樊斌)
浏览  |  Adobe PDF(2975Kb)  |  收藏  |  浏览/下载：493/182  |  提交时间：2016/10/24
Locality-sensitive Hashing (Lsh)  Semantic Similarity Search  Two-step Hashing  
LMI Conditions for Global Stability of Fractional-Order Neural Networks 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2017, 卷号: 28, 期号: 10, 页码: 2423-2433
作者:  Zhang, Shuo;  Yu, Yongguang;  Yu, Junzhi
浏览  |  Adobe PDF(3938Kb)  |  收藏  |  浏览/下载：488/175  |  提交时间：2017/01/23
Fractional Order  Generalized Projective Synchronization (Gps)  Linear Matrix Inequality (Lmi)  Neural Networks  Stability  
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
Adobe PDF(3835Kb)  |  收藏  |  浏览/下载：535/268  |  提交时间：2017/09/12
Dimensionality Reduction  Feature Selection  Sparse  Structured Sparsity  
Optimal Formation of Multirobot Systems Based on a Recurrent Neural Network 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2016, 卷号: 27, 期号: 2, 页码: 322-333
作者:  Wang, Yunpeng;  Cheng, Long;  Hou, ZengGuang;  Yu, Junzhi;  Tan, Min
浏览  |  Adobe PDF(2069Kb)  |  收藏  |  浏览/下载：346/92  |  提交时间：2016/06/14
Combinational Optimization Problem  Multirobot System  Optimal Formation  Recurrent Neural Network  Shape Theory  
MTC: A Fast and Robust Graph-Based Transductive Learning Method 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 卷号: 26, 期号: 9, 页码: 1979-1991
作者:  Zhang, Yan-Ming;  Huang, Kaizhu;  Geng, Guang-Gang;  Liu, Cheng-Lin
浏览  |  Adobe PDF(3026Kb)  |  收藏  |  浏览/下载：294/46  |  提交时间：2015/10/13
Graph-based Method  Large-scale Manifold Learning  Semisupervised Learning (Ssl)  Transductive Learning (Tl)  
Error Bounds of Adaptive Dynamic Programming Algorithms for Solving Undiscounted Optimal Control Problems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 卷号: 26, 期号: 6, 页码: 1323-1334
作者:  Liu, Derong;  Li, Hongliang;  Wang, Ding
Adobe PDF(1114Kb)  |  收藏  |  浏览/下载：277/82  |  提交时间：2015/09/17
Adaptive Critic Designs  Adaptive Dynamic Programming (Adp)  Approximate Dynamic Programming  Neural Networks  Neurodynamic Programming  Nonlinear Systems  Optimal Control  
Discriminative Least Squares Regression for Multiclass Classification and Feature Selection 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2012, 卷号: 23, 期号: 11, 页码: 1738-1754
作者:  Xiang, Shiming;  Nie, Feiping;  Meng, Gaofeng;  Pan, Chunhong;  Zhang, Changshui
浏览  |  Adobe PDF(725Kb)  |  收藏  |  浏览/下载：653/214  |  提交时间：2015/09/18
Feature Selection  Least Squares Regression  Multiclass Classification  Sparse Learning