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A Framework of Adaptive Multiscale Wavelet Decomposition for Signals on Undirected Graphs Journal article
Xianwei Zheng, Yuan Yan Tang, Jiantao Zhou. A Framework of Adaptive Multiscale Wavelet Decomposition for Signals on Undirected Graphs[J]. IEEE Transactions on Signal Processing, 2019, 67(7), 1696-1711.
Authors:  Xianwei Zheng;  Yuan Yan Tang;  Jiantao Zhou
Adobe PDF | Favorite | TC[WOS]:113 TC[Scopus]:122  IF:4.6/5.2 | Submit date：2021/03/11
Adaptive Multiscale Decomposition  Downsampling Unbalance  Graph Signal  Graph Signal Shannon Entropy  Maximum Spanning Tree (Mst)  
UM-$p$Aligner: Neural Network Based Parallel Sentence Identification Model Conference paper
Leong, C., Wong, D. F., Chao, L. S.. UM-$p$Aligner: Neural Network Based Parallel Sentence Identification Model[C], 2018, 53-58.
Authors:  Leong, C.;  Wong, D. F.;  Chao, L. S.
Favorite |  | Submit date：2022/08/19
parallel sentence classification  orthogonal denoising autoencoder  neural model  maximum entropy  
Multi-Attribute Based Fuzzy C-means in Approximated Feature Space Conference paper
Liu, Zhulin, Chen, C. L. Philip, Chen, Long, Zhoto, Jin. Multi-Attribute Based Fuzzy C-means in Approximated Feature Space[C], 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE, 2017.
Authors:  Liu, Zhulin;  Chen, C. L. Philip;  Chen, Long;  Zhoto, Jin
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2018/10/30
Fuzzy C-means  Random Features  Random Fourier Features Maps  Quasi-monte Carlo Feature Maps  Weighted Multi-kernel Fuzzy C-means  Maximum Entropy Method For Weighted Data  
Random feature based multiple kernel clustering Conference paper
Zhou J., Pan Y., Wang L., Chen C.L.P.. Random feature based multiple kernel clustering[C], 2016, 7-10.
Authors:  Zhou J.;  Pan Y.;  Wang L.;  Chen C.L.P.
Favorite | TC[WOS]:3 TC[Scopus]:3 | Submit date：2019/02/11
Kernel Clustering  Maximum-entropy Method  Multi-kernel Clustering  Random Fourier Feature  
Fuzzy clustering with the entropy of attribute weights Journal article
Zhou J., Chen L., Chen C.L.P., Zhang Y., Li H.-X.. Fuzzy clustering with the entropy of attribute weights[J]. Neurocomputing, 2016, 198, 125.
Authors:  Zhou J.;  Chen L.;  Chen C.L.P.;  Zhang Y.;  Li H.-X.
Favorite | TC[WOS]:117 TC[Scopus]:148 | Submit date：2018/10/30
Attribute-weighted Clustering  Feature Selection  Kernel Method  Maximum-entropy Regularization  
Maximum-entropy-based multiple kernel fuzzy CMeans clustering algorithm Conference paper
Zhou J., Philip Chen C.L., Chen L.. Maximum-entropy-based multiple kernel fuzzy CMeans clustering algorithm[C], 2014, 1198-1203.
Authors:  Zhou J.;  Philip Chen C.L.;  Chen L.
Favorite | TC[WOS]:12 TC[Scopus]:13 | Submit date：2019/02/11
Data Clustering  Maximum-entropy  Multiple Kernel Clustering  
Impersonal probability assessment of equipment trip probability due to voltage sag Conference paper
Wang Y., Huang Y., Ma C., Xiao X.. Impersonal probability assessment of equipment trip probability due to voltage sag[C], 2010.
Authors:  Wang Y.;  Huang Y.;  Ma C.;  Xiao X.
Favorite | TC[WOS]:0 TC[Scopus]:1 | Submit date：2019/01/16
Impersonal Evaluation  Maximum Entropy Model  Sensitive Equipment  Trip Probability  Voltage Sag  
A Maximum Entropy (ME) Based Translation Model for Chinese Characters Conversion Journal article
Fai Wong, Sam Chao, Cheong Cheong Hao, Ka Seng Leong. A Maximum Entropy (ME) Based Translation Model for Chinese Characters Conversion[J]. Advances in Computational Linguistics, Research in Computer Science, 2009, 41, 267–276.
Authors:  Fai Wong;  Sam Chao;  Cheong Cheong Hao;  Ka Seng Leong
Favorite |  | Submit date：2019/04/17
Maximum Entropy, Machine Learning,  Traditional Chinese  Chinese Translation  Natural Language Processing  Simplified Chinese