Kernel Bisecting k-means clustering for SVM training sample reduction. - Xiao-Zhang Liu; Guo-Can Feng (ICPR, 2008)

Fast training of support vector machines using top-down kernel clustering. - Xiao-Zhang Liu; Hui-Zhen Qiu (ISKE, 2008)

Gabor Feature-Based Face Recognition Using Riemannian Manifold Learning. - Xiao-Zhang Liu (PACIIA (1), 2008)

A Simple Kernel Method with Shannon Wavelet Kernel for Face Recognition. - Jingtao Fu; Xiaozhang Liu (CSO (1), 2009)

Learning Kernel in Kernel-Based LDA for Face Recognition Under Illumination Variations. - Xiao-Zhang Liu; Wen-Sheng Chen; Pong Chi Yuen; Guo-Can Feng (IEEE Signal Process. Lett., 2009)

Probable Influence of E-government on Financial Accountability in China. - Tian-Yi Chen; Xiao-Zhang Liu; Jing-Tao Fu (ICEE, 2010)

Multiple kernel discriminant analysis. - Xiao-Zhang Liu; Guo-Can Feng (ICPR, 2012)

Optimizing Weight and Threshold of BP Neural Network Using SFLA: Applications to Nonlinear Function Fitting. - Hongwei Ye; Linfang Yang; Xiaozhang Liu (EIDWT, 2013)

Kernel-Based 2D Fisher Discriminant Analysis with parameter Optimization for Face Recognition. - Xiao-Zhang Liu; Patrick S. P. Wang; Guo-Can Feng (Int. J. Pattern Recognit. Artif. Intell., 2013)

Distributed Face Recognition Using Multiple Kernel Discriminant Analysis in Wireless Sensor Networks. - Xiao-Zhang Liu; Guan Yang (Int. J. Distributed Sens. Networks, 2014)

Dual-kernel based 2D linear discriminant analysis for face recognition. - Xiaozhang Liu; Hongwei Ye (J. Ambient Intell. Humaniz. Comput., 2015)

Fisher discriminant analysis based on kernel cuboid for face recognition. - Xiao-Zhang Liu; Chen-Guang Zhang (Soft Comput., 2016)

Kernel Bilinear Discriminant Analysis for Face Recognition. - Xiao-Zhang Liu (CSE/EUC (1), 2017)

Face pose estimation based on kernelized maximum separability. - Xiao-Zhang Liu; Yu-Wei Li (Soft Comput., 2018)

Kernel-based tensor discriminant analysis with fuzzy fusion for face recognition. - Xiao-Zhang Liu; Hang-Yu Ruan (Int. J. Comput. Sci. Eng., 2019)

Kernel Optimization in SVM for Defense Against Adversarial Attacks. - Wanman Li; Xiaozhang Liu (CSS, 2020)

Video frame interpolation via optical flow estimation with image inpainting. - Xiaozhang Liu; Hui Liu 016; Yuxiu Lin (Int. J. Intell. Syst., 2020)

A game-theoretic approach of mixing different qualities of coins. - Xiaozhang Liu; Xinying Yu; Haojia Zhu; Guoyu Yang; Yilei Wang; Xiaomei Yu (Int. J. Intell. Syst., 2020)

CSRT rumor spreading model based on complex network. - Shan Ai; Sheng Hong; Xinyang Zheng; Yue Wang 058; Xiaozhang Liu (Int. J. Intell. Syst., 2021)

A computational approach for predicting drug-target interactions from protein sequence and drug substructure fingerprint information. - Yang Li 111; Xiaozhang Liu; Zhu-Hong You; Li-Ping Li 003; Jian-Xin Guo; Zheng Wang 065 (Int. J. Intell. Syst., 2021)

Querying little is enough: Model inversion attack via latent information. - Kanghua Mo; Xiaozhang Liu; Teng Huang 001; Anli Yan (Int. J. Intell. Syst., 2021)

MHAT: An efficient model-heterogenous aggregation training scheme for federated learning. - Li Hu; Hongyang Yan; Lang Li; Zijie Pan; Xiaozhang Liu; Zulong Zhang (Inf. Sci., 2021)

Dual attention guided multi-scale CNN for fine-grained image classification. - Xiaozhang Liu; Lifeng Zhang; Tao Li; Dejian Wang; Zhaojie Wang (Inf. Sci., 2021)

A Novel Pruning Method Based on Correlation Applied in Full-Connection Layer Neurons. - Shuoyu Dong; Xiaozhang Liu; Xiulai Li; GengQuan Xie; Xin Tang (ICAIS (2), 2022)

Detect Adversarial Examples by Using Feature Autoencoder. - Hongwei Ye; Xiaozhang Liu; Anli Yan; Lang Li; Xiulai Li (ICAIS (3), 2022)

Explanation-Guided Minimum Adversarial Attack. - Mingting Liu; Xiaozhang Liu; Anli Yan; Yuan Qi; Wei Li (ML4CS (1), 2022)

Discrete Wavelet Transform-Based CNN for Breast Cancer Classification from Histopathology Images. - Yuan Qi; Xiaozhang Liu; Hua Li; Mingting Liu; Wei Li (ML4CS (1), 2022)

Adversarial examples generated from sample subspace. - Xiaozhang Liu; Lang Li; Xueyang Wang; Li Hu (Comput. Stand. Interfaces, 2022)

Kernel-based adversarial attacks and defenses on support vector classification. - Wanman Li; Xiaozhang Liu; Anli Yan; Jie Yang (Digit. Commun. Networks, 2022)

Towards explainable model extraction attacks. - Anli Yan; Ruitao Hou; Xiaozhang Liu; Hongyang Yan; Teng Huang 001; Xianmin Wang (Int. J. Intell. Syst., 2022)

Feature autoencoder for detecting adversarial examples. - Hongwei Ye; Xiaozhang Liu (Int. J. Intell. Syst., 2022)

DSCAE: a denoising sparse convolutional autoencoder defense against adversarial examples. - Hongwei Ye; Xiaozhang Liu; Chunlai Li (J. Ambient Intell. Humaniz. Comput., 2022)

Zeroth-Order Gradient Approximation Based DaST for Black-Box Adversarial Attacks. - Yanfei Zhu; Yaochi Zhao; Zhuhua Hu; Xiaozhang Liu; Anli Yan (ICIC (1), 2023)

Explanation leaks: Explanation-guided model extraction attacks. - Anli Yan; Teng Huang 001; Lishan Ke; Xiaozhang Liu; Qi Chen 024; Changyu Dong (Inf. Sci., 2023)

Holistic Implicit Factor Evaluation of Model Extraction Attacks. - Anli Yan; Hongyang Yan; Li Hu; Xiaozhang Liu; Teng Huang 001 (IEEE Trans. Dependable Secur. Comput., 2023)

Explanation-based data-free model extraction attacks. - Anli Yan; Ruitao Hou; Hongyang Yan; Xiaozhang Liu (World Wide Web (WWW), 2023)

Explanation-Guided Adversarial Example Attacks. - Anli Yan; Xiaozhang Liu; Wanman Li; Hongwei Ye; Lang Li (Big Data Res., 2024)

Adaptive Threshold Learning in Frequency Domain for Classification of Breast Cancer Histopathological Images. - Yujian Liu; Xiaozhang Liu; Yuan Qi (Int. J. Intell. Syst., 2024)

Pseudo unlearning via sample swapping with hash. - Lang Li; Xiaojun Ren; Hongyang Yan; Xiaozhang Liu; Zhenxin Zhang (Inf. Sci., 2024)

Logical Reasoning in Large Language Models: A Survey. - Hanmeng Liu; Zhizhang Fu; Mengru Ding; Ruoxi Ning; Chaoli Zhang; Xiaozhang Liu; Yue Zhang 004 (CoRR, 2025)

Evaluating the Logical Reasoning Abilities of Large Reasoning Models. - Hanmeng Liu; Yiran Ding; Zhizhang Fu; Chaoli Zhang; Xiaozhang Liu; Yue Zhang 004 (CoRR, 2025)