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Distribution preserving-based deep semi-NMF for data representation Journal article
Anyong Qin, Zhuolin Tan, Xingli Tan, Yongji Wu, Cheng Jing, Yuan Yan Tang. Distribution preserving-based deep semi-NMF for data representation[J]. NEUROCOMPUTING, 2023, 524, 69-83.
Authors:  Anyong Qin;  Zhuolin Tan;  Xingli Tan;  Yongji Wu;  Cheng Jing; et al.
Favorite | TC[WOS]:2 TC[Scopus]:3  IF:5.5/5.5 | Submit date：2023/04/03
Clustering  Deep Semi-nmf  Distribution Preserving  Manifold Structure  Projected Barzilai-borwein Method  
Distribution Preserving Deep Semi-Nonnegative Matrix Factorization Conference paper
Zhuolin Tan, Anyong Qin, Yongqing Sun, Yuan Yan Tang. Distribution Preserving Deep Semi-Nonnegative Matrix Factorization[C]:IEEE, 2021, 1081-1086.
Authors:  Zhuolin Tan;  Anyong Qin;  Yongqing Sun;  Yuan Yan Tang
Favorite | TC[WOS]:2 TC[Scopus]:3 | Submit date：2022/05/13
Low-rank matrix recovery from noise via an mdl framework-based atomic norm Journal article
Qin, Anyong, Xian, Lina, Yang, Yongliang, Zhang, Taiping, Yan Tang, Yuan. Low-rank matrix recovery from noise via an mdl framework-based atomic norm[J]. Sensors (Switzerland), 2020, 20(21), 1-21.
Authors:  Qin, Anyong;  Xian, Lina;  Yang, Yongliang;  Zhang, Taiping;  Yan Tang, Yuan
Favorite | TC[WOS]:3 TC[Scopus]:3  IF:3.4/3.7 | Submit date：2021/12/06
Atomic Norm  Low-rank Matrix Recovery  Minimum Description Length Principle  Robust Principal Components Analysis  
A cost-sensitive meta-learning classifier: SPFCNN-Miner Journal article
Zhao, Linchang, Shang, Zhaowei, Qin, Anyong, Zhang, Taiping, Zhao, Ling, Wei, Yu, Tang, Yuan Yan. A cost-sensitive meta-learning classifier: SPFCNN-Miner[J]. Future Generation Computer Systems, 2019, 100, 1031-1043.
Authors:  Zhao, Linchang;  Shang, Zhaowei;  Qin, Anyong;  Zhang, Taiping;  Zhao, Ling; et al.
Favorite | TC[WOS]:3 TC[Scopus]:5  IF:6.2/5.9 | Submit date：2022/05/17
Meta Learning  Few-shot Learning  Cost-sensitive Learning  Machine Learning  Siamese Parallel Fully-connected Networks  Data Mining  
Distribution Preserving Network Embedding Conference paper
Anyong Qin, Zhaowei Shang, Taiping Zhang, Yuan Yan Tang. Distribution Preserving Network Embedding[C]:IEEE, 2019, 3562-3566.
Authors:  Anyong Qin;  Zhaowei Shang;  Taiping Zhang;  Yuan Yan Tang
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2022/05/17
Clustering  Distribution Preserving  Manifold Structure  Part-based Representation  Sparse Autoencoder  
Spectral-Spatial Sparse Subspace Clustering Based on Three-Dimensional Edge-Preserving Filtering for Hyperspectral Image Journal article
Li, Ailin, Qin, Anyong, Shang, Zhaowei, Tang, Yuan Yan. Spectral-Spatial Sparse Subspace Clustering Based on Three-Dimensional Edge-Preserving Filtering for Hyperspectral Image[J]. International Journal of Pattern Recognition and Artificial Intelligence, 2019, 33(3).
Authors:  Li, Ailin;  Qin, Anyong;  Shang, Zhaowei;  Tang, Yuan Yan
Favorite | TC[WOS]:14 TC[Scopus]:12  IF:0.9/1.0 | Submit date：2022/04/15
3d Edge-preserving Filters (3d Epfs)  Hyperspectral Images (Hsis)  Intensity Differences  Sparse Subspace Clustering (Ssc)  
Edge-Smoothing-Based Distribution Preserving Hyperspherical Embedding for Hyperspectral Image Classification Journal article
Qin, Anyong, Shang, Zhaowei, Tian, Jinyu, Zhang, Taiping, Tang, Yuan Yan, Qian, Jiye. Edge-Smoothing-Based Distribution Preserving Hyperspherical Embedding for Hyperspectral Image Classification[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2018, 11(7), 2501-2512.
Authors:  Qin, Anyong;  Shang, Zhaowei;  Tian, Jinyu;  Zhang, Taiping;  Tang, Yuan Yan; et al.
Favorite | TC[WOS]:4 TC[Scopus]:5  IF:4.7/5.0 | Submit date：2018/10/30
Dimensional Reduction  Distribution Preserving Embedding  Edge-preserving Smoothing  Hyperspectral Image (Hsi) Classification  Unit Hyperspherical Manifold  
Learning the Distribution Preserving Semantic Subspace for Clustering Journal article
Tian, Jinyu, Zhang, Taiping, Qin, Anyong, Shang, Zhaowei, Tang, Yuan Yan. Learning the Distribution Preserving Semantic Subspace for Clustering[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2017, 26(12), 5950-5965.
Authors:  Tian, Jinyu;  Zhang, Taiping;  Qin, Anyong;  Shang, Zhaowei;  Tang, Yuan Yan
Favorite | TC[WOS]:20 TC[Scopus]:22  IF:10.8/12.1 | Submit date：2018/10/30
Clustering  Distribution Preserving Indexing  Semantic Representation  Local Manifold Structure  
Using Graph-Based Ensemble Learning to Classify Imbalanced Data Conference paper
Qin, Anyong, Shang, Zhaowei, Tian, Jinyu, Zhang, Taiping, Wang, Yulong, Tang, Yuan Yan, IEEE. Using Graph-Based Ensemble Learning to Classify Imbalanced Data[C], 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE, 2017, 265-270.
Authors:  Qin, Anyong;  Shang, Zhaowei;  Tian, Jinyu;  Zhang, Taiping;  Wang, Yulong; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2018/10/30
Imbalanced Data  Ensemble Learning  Consensus Maximization  
Maximum Correntropy Criterion for Convex and Semi-Nonnegative Matrix Factorization Conference paper
Qin, Anyong, Shang, Zhaowei, Tian, Jinyu, Li, Ailin, Wang, Yulong, Tang, Yuan Yan, IEEE. Maximum Correntropy Criterion for Convex and Semi-Nonnegative Matrix Factorization[C], 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE, 2017, 1856-1861.
Authors:  Qin, Anyong;  Shang, Zhaowei;  Tian, Jinyu;  Li, Ailin;  Wang, Yulong; et al.
Favorite | TC[WOS]:4 TC[Scopus]:4 | Submit date：2018/10/30
Maximum Correntropy Criterion  Nonnegative Matrix Factorization  Clustering