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2020 – today
- 2024
[j25]Anli Yan, Xiaozhang Liu
, Wanman Li, Hongwei Ye, Lang Li:
Explanation-Guided Adversarial Example Attacks. Big Data Res. 36: 100451 (2024)- [j24]Yujian Liu, Xiaozhang Liu, Yuan Qi:
Adaptive Threshold Learning in Frequency Domain for Classification of Breast Cancer Histopathological Images. Int. J. Intell. Syst. 2024: 1-13 (2024) - [j23]Lang Li, Xiaojun Ren, Hongyang Yan, Xiaozhang Liu, Zhenxin Zhang:
Pseudo unlearning via sample swapping with hash. Inf. Sci. 662: 120135 (2024) - 2023
- [j22]Anli Yan, Teng Huang, Lishan Ke, Xiaozhang Liu, Qi Chen, Changyu Dong:
Explanation leaks: Explanation-guided model extraction attacks. Inf. Sci. 632: 269-284 (2023) - [j21]Anli Yan, Hongyang Yan, Li Hu, Xiaozhang Liu, Teng Huang:
Holistic Implicit Factor Evaluation of Model Extraction Attacks. IEEE Trans. Dependable Secur. Comput. 20(6): 4678-4689 (2023) - [j20]Anli Yan, Ruitao Hou, Hongyang Yan, Xiaozhang Liu:
Explanation-based data-free model extraction attacks. World Wide Web (WWW) 26(5): 3081-3092 (2023) - [c14]Yanfei Zhu, Yaochi Zhao, Zhuhua Hu, Xiaozhang Liu, Anli Yan:
Zeroth-Order Gradient Approximation Based DaST for Black-Box Adversarial Attacks. ICIC (1) 2023: 442-453 - 2022
- [j19]Xiaozhang Liu, Lang Li, Xueyang Wang, Li Hu:
Adversarial examples generated from sample subspace. Comput. Stand. Interfaces 82: 103634 (2022) - [j18]Wanman Li, Xiaozhang Liu, Anli Yan, Jie Yang:
Kernel-based adversarial attacks and defenses on support vector classification. Digit. Commun. Networks 8(4): 492-497 (2022) - [j17]Hongwei Ye, Xiaozhang Liu:
Feature autoencoder for detecting adversarial examples. Int. J. Intell. Syst. 37(10): 7459-7477 (2022) - [j16]Anli Yan, Ruitao Hou, Xiaozhang Liu, Hongyang Yan, Teng Huang, Xianmin Wang:
Towards explainable model extraction attacks. Int. J. Intell. Syst. 37(11): 9936-9956 (2022) - [j15]Hongwei Ye, Xiaozhang Liu, Chunlai Li:
DSCAE: a denoising sparse convolutional autoencoder defense against adversarial examples. J. Ambient Intell. Humaniz. Comput. 13(3): 1419-1429 (2022) - [c13]Shuoyu Dong, Xiaozhang Liu, Xiulai Li, GengQuan Xie, Xin Tang:
A Novel Pruning Method Based on Correlation Applied in Full-Connection Layer Neurons. ICAIS (2) 2022: 205-215 - [c12]Hongwei Ye, Xiaozhang Liu, Anli Yan, Lang Li, Xiulai Li:
Detect Adversarial Examples by Using Feature Autoencoder. ICAIS (3) 2022: 233-242 - [c11]Mingting Liu, Xiaozhang Liu, Anli Yan, Yuan Qi, Wei Li:
Explanation-Guided Minimum Adversarial Attack. ML4CS (1) 2022: 257-270 - [c10]Yuan Qi, Xiaozhang Liu, Hua Li, Mingting Liu, Wei Li:
Discrete Wavelet Transform-Based CNN for Breast Cancer Classification from Histopathology Images. ML4CS (1) 2022: 326-340 - 2021
- [j14]Yang Li, Xiaozhang Liu, Zhu-Hong You, Li-Ping Li, Jian-Xin Guo, Zheng Wang:
A computational approach for predicting drug-target interactions from protein sequence and drug substructure fingerprint information. Int. J. Intell. Syst. 36(1): 593-609 (2021) - [j13]Kanghua Mo, Xiaozhang Liu, Teng Huang, Anli Yan:
Querying little is enough: Model inversion attack via latent information. Int. J. Intell. Syst. 36(2): 681-690 (2021) - [j12]Shan Ai, Sheng Hong, Xinyang Zheng, Yue Wang, Xiaozhang Liu:
CSRT rumor spreading model based on complex network. Int. J. Intell. Syst. 36(5): 1903-1913 (2021) - [j11]Li Hu, Hongyang Yan, Lang Li, Zijie Pan, Xiaozhang Liu, Zulong Zhang:
MHAT: An efficient model-heterogenous aggregation training scheme for federated learning. Inf. Sci. 560: 493-503 (2021) - [j10]Xiaozhang Liu, Lifeng Zhang, Tao Li, Dejian Wang, Zhaojie Wang:
Dual attention guided multi-scale CNN for fine-grained image classification. Inf. Sci. 573: 37-45 (2021) - [e1]Jieren Cheng, Xiangyan Tang, Xiaozhang Liu:
Cyberspace Safety and Security - 12th International Symposium, CSS 2020, Haikou, China, December 1-3, 2020, Proceedings. Lecture Notes in Computer Science 12653, Springer 2021, ISBN 978-3-030-73670-5 [contents] - 2020
- [j9]Xiaozhang Liu, Xinying Yu, Haojia Zhu, Guoyu Yang, Yilei Wang, Xiaomei Yu:
A game-theoretic approach of mixing different qualities of coins. Int. J. Intell. Syst. 35(12): 1899-1911 (2020) - [j8]Xiaozhang Liu, Hui Liu, Yuxiu Lin:
Video frame interpolation via optical flow estimation with image inpainting. Int. J. Intell. Syst. 35(12): 2087-2102 (2020) - [c9]Wanman Li, Xiaozhang Liu:
Kernel Optimization in SVM for Defense Against Adversarial Attacks. CSS 2020: 32-42
2010 – 2019
- 2019
- [j7]Xiao-Zhang Liu, Hang-Yu Ruan:
Kernel-based tensor discriminant analysis with fuzzy fusion for face recognition. Int. J. Comput. Sci. Eng. 19(2): 293-300 (2019) - 2018
- [j6]Xiao-Zhang Liu, Yu-Wei Li:
Face pose estimation based on kernelized maximum separability. Soft Comput. 22(23): 7825-7831 (2018) - 2017
- [c8]Xiao-Zhang Liu:
Kernel Bilinear Discriminant Analysis for Face Recognition. CSE/EUC (1) 2017: 603-606 - 2016
- [j5]Xiao-Zhang Liu, Chen-Guang Zhang:
Fisher discriminant analysis based on kernel cuboid for face recognition. Soft Comput. 20(3): 831-840 (2016) - 2015
- [j4]Xiaozhang Liu, Hongwei Ye:
Dual-kernel based 2D linear discriminant analysis for face recognition. J. Ambient Intell. Humaniz. Comput. 6(5): 557-562 (2015) - 2014
- [j3]Xiao-Zhang Liu, Guan Yang:
Distributed Face Recognition Using Multiple Kernel Discriminant Analysis in Wireless Sensor Networks. Int. J. Distributed Sens. Networks 10 (2014) - 2013
- [j2]Xiao-Zhang Liu, Patrick S. P. Wang, Guo-Can Feng:
Kernel-Based 2D Fisher Discriminant Analysis with parameter Optimization for Face Recognition. Int. J. Pattern Recognit. Artif. Intell. 27(8) (2013) - [c7]Hongwei Ye, Linfang Yang, Xiaozhang Liu:
Optimizing Weight and Threshold of BP Neural Network Using SFLA: Applications to Nonlinear Function Fitting. EIDWT 2013: 211-214 - 2012
- [c6]Xiao-Zhang Liu, Guo-Can Feng:
Multiple kernel discriminant analysis. ICPR 2012: 1691-1694 - 2010
- [c5]Tian-Yi Chen, Xiao-Zhang Liu, Jing-Tao Fu:
Probable Influence of E-government on Financial Accountability in China. ICEE 2010: 501-503
2000 – 2009
- 2009
- [j1]Xiao-Zhang Liu, Wen-Sheng Chen, Pong Chi Yuen, Guo-Can Feng:
Learning Kernel in Kernel-Based LDA for Face Recognition Under Illumination Variations. IEEE Signal Process. Lett. 16(12): 1019-1022 (2009) - [c4]Jingtao Fu, Xiaozhang Liu:
A Simple Kernel Method with Shannon Wavelet Kernel for Face Recognition. CSO (1) 2009: 434-437 - 2008
- [c3]Xiao-Zhang Liu, Guo-Can Feng:
Kernel Bisecting k-means clustering for SVM training sample reduction. ICPR 2008: 1-4 - [c2]Xiao-Zhang Liu, Hui-Zhen Qiu:
Fast training of support vector machines using top-down kernel clustering. ISKE 2008: 968-971 - [c1]Xiao-Zhang Liu:
Gabor Feature-Based Face Recognition Using Riemannian Manifold Learning. PACIIA (1) 2008: 386-389
Coauthor Index
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