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Who is King in Factor Zoo? Case of the Chinese Stock Market Journal
创刊日期: 2020, 出版者: Journal of Prediction Markets,
Authors:  So, M. S. Simon;  Bu, Z. Y. Eunice
Favorite |  | Submit date：2022/08/27
Who is King in Factor Zoo? Case of the Chinese Stock Market Journal article
Simon M. S. So, Eunice Z. Y. Bu. Who is King in Factor Zoo? Case of the Chinese Stock Market[J]. Journal of Prediction Markets, 2020, 14(2), 77-101.
Authors:  Simon M. S. So;  Eunice Z. Y. Bu
Favorite |  | Submit date：2022/08/30
Unsupervised Learning 3-D Local Feature from Raw Voxels based on A Novel Permutation Voxelization Strategy- Journal article
Han, Z. Z., Liu, Z. B., Han, J. W., Vong, C. M., Bu, S. H., Chen, C. L. P.. Unsupervised Learning 3-D Local Feature from Raw Voxels based on A Novel Permutation Voxelization Strategy-[J]. IEEE Transactions on Cybernetics (SCI-E) (Accepted for Publication), 2019, 2168-2267.
Authors:  Han, Z. Z.;  Liu, Z. B.;  Han, J. W.;  Vong, C. M.;  Bu, S. H.; et al.
Favorite |  | Submit date：2022/08/09
3-D local features  3-D voxelization  deep learning  stacked sparse autoencoder (SSAE)  unsupervised feature learning  
Unsupervised Learning of 3-D Local Features From Raw Voxels Based on a Novel Permutation Voxelization Strategy Journal article
Han Z., Liu Z., Han J., Vong C.-M., Bu S., Chen C.L.P.. Unsupervised Learning of 3-D Local Features From Raw Voxels Based on a Novel Permutation Voxelization Strategy[J]. IEEE Transactions on Cybernetics, 2019, 49(2), 481-494.
Authors:  Han Z.;  Liu Z.;  Han J.;  Vong C.-M.;  Bu S.; et al.
Favorite | TC[WOS]:31 TC[Scopus]:31  IF:9.4/10.3 | Submit date：2019/02/11
3-d Local Features  3-d Voxelization  Deep Learning  Stacked Sparse Autoencoder (Ssae)  Unsupervised Feature Learning  
A Fully Integrated Low-Dropout Regulator with Differentiator-Based Active Zero Compensation Journal article
Bu S., Leung K.N., Lu Y., Guo J., Zheng Y.. A Fully Integrated Low-Dropout Regulator with Differentiator-Based Active Zero Compensation[J]. IEEE Transactions on Circuits and Systems I: Regular Papers, 2018, 65(10), 3578-3591.
Authors:  Bu S.;  Leung K.N.;  Lu Y.;  Guo J.;  Zheng Y.
Favorite | TC[WOS]:33 TC[Scopus]:39 | Submit date：2019/02/14
Area-efficient  Current Density  Frequency Compensation  Low-dropout Regulator  Miller Compensation  Power Management  
Deep Spatiality: Unsupervised Learning of Spatially-Enhanced Global and Local 3D Features by Deep Neural Network with Coupled Softmax Journal article
Han Z., Liu Z., Vong C.-M., Liu Y.-S., Bu S., Han J., Chen C.L.P.. Deep Spatiality: Unsupervised Learning of Spatially-Enhanced Global and Local 3D Features by Deep Neural Network with Coupled Softmax[J]. IEEE Transactions on Image Processing, 2018, 27(6), 3049-3063.
Authors:  Han Z.;  Liu Z.;  Vong C.-M.;  Liu Y.-S.;  Bu S.; et al.
Favorite | TC[WOS]:37 TC[Scopus]:43 | Submit date：2019/02/11
Coupled Softmax  Deep Spatial  Directed Circular Graph  Spatially-enhanced 3d Features  
Deep Spatiality: Unsupervised Learning of Spatially-Enhanced Global and Local 3D Features by Deep Neural Network with Coupled Softmax Journal article
Han, Z. Z., Liu, Z. B., Vong, C. M., Liu, Y. S., Bu, S. H., Han, J. W., Chen, C. L. P.. Deep Spatiality: Unsupervised Learning of Spatially-Enhanced Global and Local 3D Features by Deep Neural Network with Coupled Softmax[J]. IEEE Transactions on Image Processing (SCI-E), 2018, 3049-3063.
Authors:  Han, Z. Z.;  Liu, Z. B.;  Vong, C. M.;  Liu, Y. S.;  Bu, S. H.; et al.
Favorite |   IF:10.8/12.1 | Submit date：2022/08/09
Deep spatial  spatially-enhanced 3D features  directed circular graph  coupled softmax  
Mesh Convolutional Restricted Boltzmann Machines for Unsupervised Learning of Features with Structure Preservation on 3D Meshes Journal article
Han, Z., Liu, Z., Han, J., Vong, C. M., Bu, S., Chen, C. L.. Mesh Convolutional Restricted Boltzmann Machines for Unsupervised Learning of Features with Structure Preservation on 3D Meshes[J]. IEEE Transactions on Neural Networks and Learning Systems (SCI-E), 2017, 2268-2281.
Authors:  Han, Z.;  Liu, Z.;  Han, J.;  Vong, C. M.;  Bu, S.; et al.
Favorite |   IF:10.2/10.4 | Submit date：2022/08/09
3D mesh  Laplace-Beltrami operator  Mesh Convolutional Restricted Boltzman Machines  Mesh Convolutional Deep Belief Networks  
Mesh Convolutional Restricted Boltzmann Machines for Unsupervised Learning of Features with Structure Preservation on 3-D Meshes Journal article
Han Z., Liu Z., Han J., Vong C.-M., Bu S., Chen C.L.P.. Mesh Convolutional Restricted Boltzmann Machines for Unsupervised Learning of Features with Structure Preservation on 3-D Meshes[J]. IEEE Transactions on Neural Networks and Learning Systems, 2017, 28(10), 2268-2281.
Authors:  Han Z.;  Liu Z.;  Han J.;  Vong C.-M.;  Bu S.; et al.
Favorite | TC[WOS]:44 TC[Scopus]:45 | Submit date：2019/02/11
3-d Mesh  Laplace-beltrami Operator  Mesh Convolutional Deep Belief Networks (Mcdbns)  Mesh Convolutional Restricted Boltzmann Machines (Mcrbms)  
Unsupervised 3D local Feature Learning by Circle Convolutional Restricted Boltzmann Machine Journal article
Han, Z., Liu, Z., Han, J., Vong, C. M., Bu, S., Li, X.. Unsupervised 3D local Feature Learning by Circle Convolutional Restricted Boltzmann Machine[J]. IEEE Transactions on Image Processing (SCI-E), 2016, 5331-5344.
Authors:  Han, Z.;  Liu, Z.;  Han, J.;  Vong, C. M.;  Bu, S.; et al.
Favorite |   IF:10.8/12.1 | Submit date：2022/08/09
Three-dimensional displays  Shape  Machine learning  Convolution  Solid modeling  Feature extraction  Two dimensional displays