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Hyperspectral Unmixing Using Nonlocal Similarity-Regularized Low-Rank Tensor Factorization 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60
作者:  Yuan, Yuan;  Dong, Le;  Li, Xuelong
Adobe PDF(5662Kb)  |  收藏  |  浏览/下载：226/0  |  提交时间：2022/01/18
Tensors  TV  Hyperspectral imaging  Data models  Task analysis  Optimization  Data mining  Hyperspectral unmixing  low tensor rank  nonlocal similarity  nonnegative tensor factorization (NTF)  
Supervised Dimensionality Reduction Methods via Recursive Regression 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 9, 页码: 3269-3279
作者:  Liu, Yun;  Zhang, Rui;  Nie, Feiping;  Li, Xuelong;  Ding, Chris
Adobe PDF(1723Kb)  |  收藏  |  浏览/下载：192/1  |  提交时间：2020/10/23
Dimensionality reduction  Linear discriminant analysis  Eigenvalues and eigenfunctions  Learning systems  Computer science  Optical imaging  Optics  Optimal scaling (OS)  orthogonal least squares regression (OLSR)  orthogonal linear discriminant analysis (OLDA)  recursive regression  supervised dimensionality reduction  
Spectral Clustering by Joint Spectral Embedding and Spectral Rotation 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 1, 页码: 247-258
作者:  Pang, Yanwei;  Xie, Jin;  Nie, Feiping;  Li, Xuelong
Adobe PDF(2521Kb)  |  收藏  |  浏览/下载：208/0  |  提交时间：2020/03/06
Normalized cut (Ncut)  spectral clustering  spectral rotation  
An efficient framework for unsupervised feature selection 期刊论文
NEUROCOMPUTING, 2019, 卷号: 366, 页码: 194-207
作者:  Zhang, Han;  Zhang, Rui;  Nie, Feiping;  Li, Xuelong
Adobe PDF(2196Kb)  |  收藏  |  浏览/下载：265/4  |  提交时间：2019/10/18
Efficient unsupervised feature selection  Bipartite graph  Discrete indicator matrix  Uncorrelated regression model  
Robust Subspace Clustering by Cauchy Loss Function 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 7, 页码: 2067-2078
作者:  Li, Xuelong;  Lu, Quanmao;  Dong, Yongsheng;  Tao, Dacheng
Adobe PDF(3374Kb)  |  收藏  |  浏览/下载：261/0  |  提交时间：2019/07/17
Cauchy loss function (CLF)  grouping effect  noise suppression  similarity matrix  subspace clustering  
Similarity Constrained Convex Nonnegative Matrix Factorization for Hyperspectral Anomaly Detection 期刊论文
IEEE Transactions on Geoscience and Remote Sensing, 2019, 卷号: 57, 期号: 7, 页码: 4810-4822
作者:  Zhang, Wuxia;  Lu, Xiaoqiang;  Li, Xuelong
Adobe PDF(2142Kb)  |  收藏  |  浏览/下载：214/0  |  提交时间：2019/07/17
Convex nonnegative matrix factorization (CNMF)  hyperspectral anomaly detection  hyperspectral imagery  similarity constrained  
Low-Rank 2-D Neighborhood Preserving Projection for Enhanced Robust Image Representation 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2019, 卷号: 49, 期号: 5, 页码: 1859–1872
作者:  Lu, Yuwu;  Lai, Zhihui;  Li, Xuelong;  Wong, Wai Keung;  Yuan, Chun;  Zhang, David
Adobe PDF(1718Kb)  |  收藏  |  浏览/下载：234/0  |  提交时间：2019/04/12
2-D neighborhood preserving projection (2DNPP)  image representation  low-rank  robust feature extraction  
Flexible Affinity Matrix Learning for Unsupervised and Semisupervised Classification 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 4, 页码: 1133-1149
作者:  Fang, Xiaozhao;  Han, Na;  Wong, Wai Keung;  Teng, Shaohua;  Wu, Jigang;  Xie, Shengli;  Li, Xuelong
Adobe PDF(4698Kb)  |  收藏  |  浏览/下载：261/0  |  提交时间：2019/04/17
Affinity matrix  clustering  low-rank representation (LRR)  sparse representation  
Structurally Incoherent Low-Rank Nonnegative Matrix Factorization for Image Classification 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2018, 卷号: 27, 期号: 11, 页码: 5248-5260
作者:  Lu, Yuwu;  Yuan, Chun;  Zhu, Wenwu;  Li, Xuelong
Adobe PDF(2165Kb)  |  收藏  |  浏览/下载：271/1  |  提交时间：2018/09/11
Nmf  Structurally Incoherent  Low-rank  Image Classification  
Matrix-Regularized Multiple Kernel Learning via (r, p) Norms 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 10, 页码: 4997-5007
作者:  Han, Yina;  Yang, Yixin;  Li, Xuelong;  Liu, Qingyu;  Ma, Yuanliang
Adobe PDF(1836Kb)  |  收藏  |  浏览/下载：155/0  |  提交时间：2018/10/23
Generalization Bound  Matrix Regularization  Multiple Kernel Learning (Mkl)  Support Vector Machine (Svm)