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A Gaussian Process Based Method with Deep Kernel Learning for Pricing High-Dimensional American Options Journal article
Zhuang, Jirong, Ding, Deng, Lu, Weiguo, Wu, Xuan, Yuan, Gangnan. A Gaussian Process Based Method with Deep Kernel Learning for Pricing High-Dimensional American Options[J]. Computational Economics, 2025.
Authors:  Zhuang, Jirong;  Ding, Deng;  Lu, Weiguo;  Wu, Xuan;  Yuan, Gangnan
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:1.9/1.8 | Submit date：2025/01/22
Deep Kernel Learning  Gaussian Process  High-dimensional American Option  Machine Learning  Regression Based Monte Carlo Method  
The impact of isolation kernel on agglomerative hierarchical clustering algorithms Journal article
Han,Xin, Zhu,Ye, Ting,Kai Ming, Li,Gang. The impact of isolation kernel on agglomerative hierarchical clustering algorithms[J]. Pattern Recognition, 2023, 139, 109517.
Authors:  Han,Xin;  Zhu,Ye;  Ting,Kai Ming;  Li,Gang
Favorite | TC[WOS]:7 TC[Scopus]:9  IF:7.5/7.6 | Submit date：2023/08/03
Agglomerative Hierarchical Clustering  Dendrogram Purity  Gaussian Kernel  Isolation Kernel  Varied Densities  
Gaussian process image classification based on multi-layer convolution kernel function Journal article
Xu, Lixiang, Zhou, Biao, Li, Xinlu, Wu, Zhize, Chen, Yan, Wang, Xiaofeng, Tang, Yuanyan. Gaussian process image classification based on multi-layer convolution kernel function[J]. NEUROCOMPUTING, 2022, 480, 99-109.
Authors:  Xu, Lixiang;  Zhou, Biao;  Li, Xinlu;  Wu, Zhize;  Chen, Yan; et al.
Favorite | TC[WOS]:9 TC[Scopus]:12  IF:5.5/5.5 | Submit date：2022/05/04
Convolution Kernel Function  Gaussian Process  Image Classification  Multi-layer Kernel  
Hybrid forecasting method for wind power integrating spatial correlation and corrected numerical weather prediction Journal article
Hu, Shuai, Xiang, Yue, Zhang, Hongcai, Xie, Shanyi, Li, Jianhua, Gu, Chenghong, Sun, Wei, Liu, Junyong. Hybrid forecasting method for wind power integrating spatial correlation and corrected numerical weather prediction[J]. Applied Energy, 2021, 293(116951).
Authors:  Hu, Shuai;  Xiang, Yue;  Zhang, Hongcai;  Xie, Shanyi;  Li, Jianhua; et al.
Favorite | TC[WOS]:77 TC[Scopus]:97  IF:10.1/10.4 | Submit date：2021/09/09
Wind Power Forecasting  Hybrid Model  Gaussian Process  Numerical Weather Prediction  Spatial Correlation  Kernel Function  
Shared Autoencoder Gaussian Process Latent Variable Model for Visual Classification Journal article
Li, Jinxing, Zhang, Bob, Zhang, David. Shared Autoencoder Gaussian Process Latent Variable Model for Visual Classification[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 29(9), 4272-4286.
Authors:  Li, Jinxing;  Zhang, Bob;  Zhang, David
Favorite | TC[WOS]:15 TC[Scopus]:24  IF:10.2/10.4 | Submit date：2018/10/30
Autoencoder  Discriminative  Gaussian Process (Gp)  Kernel  Latent Variable Model  Multiview  
Non-rigid visual object tracking using user-defined marker and Gaussian kernel Journal article
Huang,Guoheng, Pun,Chi Man, Lin,Cong, Zhou,Yicong. Non-rigid visual object tracking using user-defined marker and Gaussian kernel[J]. Multimedia Tools and Applications, 2016, 75(10), 5473-5492.
Authors:  Huang,Guoheng;  Pun,Chi Man;  Lin,Cong;  Zhou,Yicong
Favorite | TC[WOS]:4 TC[Scopus]:5  IF:3.0/2.9 | Submit date：2021/03/11
Gaussian Kernel  Interactive Segmentation  Non-rigid  Object Tracking  Superpixel  
Video object tracking using interactive segmentation and superpixel based Gaussian kernel Conference paper
Huang G., Pun C.-M., Lin C.. Video object tracking using interactive segmentation and superpixel based Gaussian kernel[C], 2015, 450-453.
Authors:  Huang G.;  Pun C.-M.;  Lin C.
Favorite | TC[WOS]:1 TC[Scopus]:1 | Submit date：2019/02/14
Gaussian Kernel  Interactive Segmentation  Non-rigid  Object Tracking  Superpixel  
Non-rigid visual object tracking using user-defined marker and Gaussian kernel Journal article
Huang Guoheng, Pun C.-M., Lin Cong, Zhou Yicong. Non-rigid visual object tracking using user-defined marker and Gaussian kernel[J]. Multimedia Tools and Applications, 2015, 75(10), 5473-5492.
Authors:  Huang Guoheng;  Pun C.-M.;  Lin Cong;  Zhou Yicong
Favorite | TC[WOS]:4 TC[Scopus]:5 | Submit date：2018/12/21
Gaussian Kernel  Interactive Segmentation  Non-rigid  Object Tracking  Superpixel  
Support vector machine adapted Tikhonov regularization method to solve Dirichlet problem Journal article
Mo Y., Qian T.. Support vector machine adapted Tikhonov regularization method to solve Dirichlet problem[J]. Applied Mathematics and Computation, 2014, 245, 509-519.
Authors:  Mo Y.;  Qian T.
Favorite | TC[WOS]:10 TC[Scopus]:9 | Submit date：2019/02/11
Dirichlet Problem  Gaussian Rkhs  Reproducing Kernel  Sobolev Space  Support Vector Machine  Tikhonov Regularization