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2020 – today
- 2024
[c56]Caridad Arroyo Arevalo, Sayedeh Leila Noorbakhsh, Yun Dong, Yuan Hong, Binghui Wang:
Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning against Attribute Inference Attacks. AAAI 2024: 10909-10917- [c55]Yintao Zhou, Meng Pang, Wei Huang, Binghui Wang:
Early Diagnosing Parkinson's Disease Via a Deep Learning Model Based on Augmented Facial Expression Data. ICASSP 2024: 1621-1625 - [c54]Zaishuo Xia, Han Yang, Binghui Wang, Jinyuan Jia:
GNNCert: Deterministic Certification of Graph Neural Networks against Adversarial Perturbations. ICLR 2024 - [c53]Meng Pang, Binghui Wang, Nanrun Zhou, Yintao Zhou, Wei Huang:
Reconstructing Prototype From Contaminated Face With Variations Across Heterogeneous Domains. ICME 2024: 1-6 - [c52]Jiate Li, Meng Pang, Yun Dong, Jinyuan Jia, Binghui Wang:
Graph Neural Network Explanations are Fragile. ICML 2024 - [c51]Xinyu Zhang, Hanbin Hong, Yuan Hong, Peng Huang, Binghui Wang, Zhongjie Ba, Kui Ren:
Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks. SP 2024: 2920-2938 - [c50]Yansong Gao, Huming Qiu, Zhi Zhang, Binghui Wang, Hua Ma, Alsharif Abuadbba, Minhui Xue, Anmin Fu, Surya Nepal:
DeepTheft: Stealing DNN Model Architectures through Power Side Channel. SP 2024: 3311-3326 - [c49]Sayedeh Leila Noorbakhsh, Binghui Zhang, Yuan Hong, Binghui Wang:
Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks. USENIX Security Symposium 2024 - [c48]Binghui Wang
, Minhua Lin, Tianxiang Zhou, Pan Zhou, Ang Li, Meng Pang, Hai Helen Li, Yiran Chen:
Efficient, Direct, and Restricted Black-Box Graph Evasion Attacks to Any-Layer Graph Neural Networks via Influence Function. WSDM 2024: 693-701 - [i46]Wei Zou, Runpeng Geng, Binghui Wang, Jinyuan Jia:
PoisonedRAG: Knowledge Poisoning Attacks to Retrieval-Augmented Generation of Large Language Models. CoRR abs/2402.07867 (2024) - [i45]Sayedeh Leila Noorbakhsh, Binghui Zhang, Yuan Hong, Binghui Wang:
Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks. CoRR abs/2403.02116 (2024) - [i44]Jane Downer, Ren Wang, Binghui Wang:
Securing GNNs: Explanation-Based Identification of Backdoored Training Graphs. CoRR abs/2403.18136 (2024) - [i43]Jiate Li, Meng Pang, Yun Dong, Jinyuan Jia, Binghui Wang:
Graph Neural Network Explanations are Fragile. CoRR abs/2406.03193 (2024) - [i42]Yuxin Yang, Qiang Li, Jinyuan Jia, Yuan Hong, Binghui Wang:
Distributed Backdoor Attacks on Federated Graph Learning and Certified Defenses. CoRR abs/2407.08935 (2024) - [i41]Arman Behnam, Binghui Wang:
Graph Neural Network Causal Explanation via Neural Causal Models. CoRR abs/2407.09378 (2024) - [i40]Shuya Feng, Meisam Mohammady, Hanbin Hong, Shenao Yan, Ashish Kundu, Binghui Wang, Yuan Hong:
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence. CoRR abs/2407.14710 (2024) - [i39]Yuxin Yang, Qiang Li, Chenfei Nie, Yuan Hong, Meng Pang, Binghui Wang:
A Learning-Based Attack Framework to Break SOTA Poisoning Defenses in Federated Learning. CoRR abs/2407.15267 (2024) - [i38]Chenfei Nie, Qiang Li, Yuxin Yang, Yuede Ji, Binghui Wang:
Efficient Byzantine-Robust and Provably Privacy-Preserving Federated Learning. CoRR abs/2407.19703 (2024) - [i37]Zifan Wang, Binghui Zhang, Meng Pang, Yuan Hong, Binghui Wang:
Understanding Data Reconstruction Leakage in Federated Learning from a Theoretical Perspective. CoRR abs/2408.12119 (2024) - [i36]Ruo Yang, Binghui Wang, Mustafa Bilgic:
Leveraging Local Structure for Improving Model Explanations: An Information Propagation Approach. CoRR abs/2409.16429 (2024) - 2023
- [j12]Binghui Wang, Yinglei Teng, Vincent K. N. Lau, Zhu Han:
CCA-Net: A Lightweight Network Using Criss-Cross Attention for CSI Feedback. IEEE Commun. Lett. 27(7): 1879-1883 (2023) - [j11]Meng Pang, Binghui Wang, Mang Ye, Yiu-ming Cheung, Yiran Chen, Bihan Wen:
DisP+V: A Unified Framework for Disentangling Prototype and Variation From Single Sample per Person. IEEE Trans. Neural Networks Learn. Syst. 34(2): 867-881 (2023) - [c47]Binghui Wang, Meng Pang, Yun Dong:
Turning Strengths into Weaknesses: A Certified Robustness Inspired Attack Framework against Graph Neural Networks. CVPR 2023: 16394-16403 - [c46]Ruo Yang, Binghui Wang, Mustafa Bilgic:
IDGI: A Framework to Eliminate Explanation Noise from Integrated Gradients. CVPR 2023: 23725-23734 - [c45]Wenjie Qu, Youqi Li, Binghui Wang:
A Certified Radius-Guided Attack Framework to Image Segmentation Models. EuroS&P 2023: 200-220 - [c44]Yaxin Yu, Yinglei Teng, Binghui Wang, An Liu, Vincent Lau:
M-Net: A Lightweight Network Based on Multilayer Perceptron for Massive MIMO CSI Feedback. GLOBECOM (Workshops) 2023: 26-31 - [c43]Likun Zhang, Yahong Chen, Ang Li, Binghui Wang, Yiran Chen, Fenghua Li, Jin Cao, Ben Niu:
Interpreting Disparate Privacy-Utility Tradeoff in Adversarial Learning via Attribute Correlation. WACV 2023: 4690-4698 - [i35]Binghui Wang, Meng Pang, Yun Dong:
Turning Strengths into Weaknesses: A Certified Robustness Inspired Attack Framework against Graph Neural Networks. CoRR abs/2303.06199 (2023) - [i34]Ruo Yang, Binghui Wang, Mustafa Bilgic:
IDGI: A Framework to Eliminate Explanation Noise from Integrated Gradients. CoRR abs/2303.14242 (2023) - [i33]Wenjie Qu, Youqi Li, Binghui Wang:
A Certified Radius-Guided Attack Framework to Image Segmentation Models. CoRR abs/2304.02693 (2023) - [i32]Xinyu Zhang, Hanbin Hong, Yuan Hong, Peng Huang, Binghui Wang, Zhongjie Ba, Kui Ren:
Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks. CoRR abs/2307.16630 (2023) - [i31]Yansong Gao, Huming Qiu, Zhi Zhang, Binghui Wang, Hua Ma, Alsharif Abuadbba, Minhui Xue, Anmin Fu, Surya Nepal:
DeepTheft: Stealing DNN Model Architectures through Power Side Channel. CoRR abs/2309.11894 (2023) - [i30]Caridad Arroyo Arevalo, Sayedeh Leila Noorbakhsh, Yun Dong, Yuan Hong, Binghui Wang:
Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning Against Attribute Inference Attacks. CoRR abs/2312.06989 (2023) - 2022
- [j10]Meng Pang, Binghui Wang, Siyu Huang, Yiu-Ming Cheung, Bihan Wen:
A Unified Framework for Bidirectional Prototype Learning From Contaminated Faces Across Heterogeneous Domains. IEEE Trans. Inf. Forensics Secur. 17: 1544-1557 (2022) - [c42]Nuo Xu, Binghui Wang, Ran Ran, Wujie Wen, Parv Venkitasubramaniam:
NeuGuard: Lightweight Neuron-Guided Defense against Membership Inference Attacks. ACSAC 2022: 669-683 - [c41]Binghui Wang, Tianchen Zhou, Song Li, Yinzhi Cao, Neil Zhenqiang Gong:
GraphTrack: A Graph-based Cross-Device Tracking Framework. AsiaCCS 2022: 82-96 - [c40]Meng Pang, Binghui Wang, Shengbo Chen, Yiu-ming Cheung, Rong Zou, Wei Huang:
Cross-domain Prototype Learning from Contaminated Faces via Disentangling Latent Factors. CIKM 2022: 4369-4373 - [c39]Binghui Wang, Youqi Li, Pan Zhou:
Bandits for Structure Perturbation-based Black-box Attacks to Graph Neural Networks with Theoretical Guarantees. CVPR 2022: 13369-13377 - [c38]Hanbin Hong, Binghui Wang, Yuan Hong:
UniCR: Universally Approximated Certified Robustness via Randomized Smoothing. ECCV (5) 2022: 86-103 - [c37]Binghui Wang, Ang Li, Meng Pang, Hai Li, Yiran Chen:
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs. ICDM 2022: 498-507 - [c36]Jinyuan Jia, Binghui Wang, Xiaoyu Cao, Hongbin Liu, Neil Zhenqiang Gong:
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations. ICLR 2022 - [c35]Yijue Wang, Jieren Deng, Dan Guo, Chenghong Wang, Xianrui Meng, Hang Liu, Chao Shang, Binghui Wang, Qin Cao, Caiwen Ding, Sanguthevar Rajasekaran:
Variance of the Gradient Also Matters: Privacy Leakage from Gradients. IJCNN 2022: 1-8 - [c34]Haiyang Luo, Zhe Sun, Yunqing Sun, Ang Li, Binghui Wang, Jin Cao, Ben Niu:
SmartCircles: A Benefit-Evaluation-Based Privacy Policy Recommender for Customized Photo Sharing. SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta 2022: 2340-2347 - [i29]Binghui Wang, Tianchen Zhou, Song Li, Yinzhi Cao, Neil Zhenqiang Gong:
GraphTrack: A Graph-based Cross-Device Tracking Framework. CoRR abs/2203.06833 (2022) - [i28]Binghui Wang, Youqi Li, Pan Zhou:
Bandits for Structure Perturbation-based Black-box Attacks to Graph Neural Networks with Theoretical Guarantees. CoRR abs/2205.03546 (2022) - [i27]Nuo Xu, Binghui Wang, Ran Ran, Wujie Wen, Parv Venkitasubramaniam:
NeuGuard: Lightweight Neuron-Guided Defense against Membership Inference Attacks. CoRR abs/2206.05565 (2022) - [i26]Hanbin Hong, Binghui Wang, Yuan Hong:
UniCR: Universally Approximated Certified Robustness via Randomized Smoothing. CoRR abs/2207.02152 (2022) - 2021
- [j9]Meng Pang, Binghui Wang, Yiu-ming Cheung, Yiran Chen, Bihan Wen:
VD-GAN: A Unified Framework for Joint Prototype and Representation Learning From Contaminated Single Sample per Person. IEEE Trans. Inf. Forensics Secur. 16: 2246-2259 (2021) - [j8]Tong Wu, Pan Zhou, Binghui Wang, Ang Li, Xueming Tang, Zichuan Xu, Kai Chen, Xiaofeng Ding:
Joint Traffic Control and Multi-Channel Reassignment for Core Backbone Network in SDN-IoT: A Multi-Agent Deep Reinforcement Learning Approach. IEEE Trans. Netw. Sci. Eng. 8(1): 231-245 (2021) - [c33]Binghui Wang, Jinyuan Jia, Neil Zhenqiang Gong:
Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks. AAAI 2021: 10093-10101 - [c32]Zijie Yang, Binghui Wang, Haoran Li, Dong Yuan, Zhuotao Liu, Neil Zhenqiang Gong, Chang Liu, Qi Li, Xiao Liang, Shaofeng Hu:
On Detecting Growing-Up Behaviors of Malicious Accounts in Privacy-Centric Mobile Social Networks. ACSAC 2021: 297-310 - [c31]Jinyuan Jia, Binghui Wang, Neil Zhenqiang Gong:
Robust and Verifiable Information Embedding Attacks to Deep Neural Networks via Error-Correcting Codes. AsiaCCS 2021: 2-13 - [c30]Jiaming Mu, Binghui Wang, Qi Li, Kun Sun, Mingwei Xu, Zhuotao Liu:
A Hard Label Black-box Adversarial Attack Against Graph Neural Networks. CCS 2021: 108-125 - [c29]Jingwei Sun, Ang Li, Binghui Wang, Huanrui Yang, Hai Li, Yiran Chen:
Soteria: Provable Defense Against Privacy Leakage in Federated Learning From Representation Perspective. CVPR 2021: 9311-9319 - [c28]Houxiang Fan, Binghui Wang, Pan Zhou, Ang Li, Zichuan Xu, Cai Fu, Hai Li, Yiran Chen:
Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs. HPCC/DSS/SmartCity/DependSys 2021: 933-940 - [c27]Meng Pang, Binghui Wang, Mang Ye, Yiran Chen, Bihan Wen:
Disentangling Prototype and Variation for Single Sample Face Recognition. ICME 2021: 1-6 - [c26]Ang Li, Jingwei Sun, Binghui Wang, Lin Duan, Sicheng Li, Yiran Chen, Hai Li:
LotteryFL: Empower Edge Intelligence with Personalized and Communication-Efficient Federated Learning. SEC 2021: 68-79 - [c25]Binghui Wang, Haigang Yang, Yiping Jia:
A 3-6GHz 5-to-512 Multiplier Adaptive Fast-Locking Self-Biased PLL in 28nm CMOS. ISCAS 2021: 1-5 - [c24]Binghui Wang, Jinyuan Jia, Xiaoyu Cao, Neil Zhenqiang Gong:
Certified Robustness of Graph Neural Networks against Adversarial Structural Perturbation. KDD 2021: 1645-1653 - [c23]Binghui Wang, Jiayi Guo, Ang Li, Yiran Chen, Hai Li:
Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspective. KDD 2021: 1667-1676 - [c22]Xiao Liang, Zheng Yang, Binghui Wang, Shaofeng Hu, Zijie Yang, Dong Yuan, Neil Zhenqiang Gong, Qi Li, Fang He:
Unveiling Fake Accounts at the Time of Registration: An Unsupervised Approach. KDD 2021: 3240-3250 - [c21]Qiming Wu, Zhikang Zou, Pan Zhou, Xiaoqing Ye, Binghui Wang, Ang Li:
Towards Adversarial Patch Analysis and Certified Defense against Crowd Counting. ACM Multimedia 2021: 2195-2204 - [c20]Zaixi Zhang, Jinyuan Jia, Binghui Wang, Neil Zhenqiang Gong:
Backdoor Attacks to Graph Neural Networks. SACMAT 2021: 15-26 - [i25]Qiming Wu, Zhikang Zou, Pan Zhou, Xiaoqing Ye, Binghui Wang, Ang Li:
Towards Adversarial Patch Analysis and Certified Defense against Crowd Counting. CoRR abs/2104.10868 (2021) - [i24]Binghui Wang, Jiayi Guo, Ang Li, Yiran Chen, Hai Li:
Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspective. CoRR abs/2107.01475 (2021) - [i23]Jiaming Mu, Binghui Wang, Qi Li, Kun Sun, Mingwei Xu, Zhuotao Liu:
A Hard Label Black-box Adversarial Attack Against Graph Neural Networks. CoRR abs/2108.09513 (2021) - [i22]Bingbing Li, Hongwu Peng, Rajat Sainju, Junhuan Yang, Lei Yang, Yueying Liang, Weiwen Jiang, Binghui Wang, Hang Liu, Caiwen Ding:
Detecting Gender Bias in Transformer-based Models: A Case Study on BERT. CoRR abs/2110.15733 (2021) - 2020
- [j7]Meng Pang, Yiu-Ming Cheung, Binghui Wang, Jian Lou:
Synergistic Generic Learning for Face Recognition From a Contaminated Single Sample per Person. IEEE Trans. Inf. Forensics Secur. 15: 195-209 (2020) - [c19]Jianwei Zhao, Guangjun Zhao, Biao Pan, Meng Zhou, Lei Song, Binghui Wang, Jie Zhang:
An Intelligent Service Method for Grid Spatio-Temporal Big Data Based on Beidou. ICITEE 2020: 574-578 - [c18]Jinyuan Jia, Xiaoyu Cao, Binghui Wang, Neil Zhenqiang Gong:
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing. ICLR 2020 - [c17]Luke Myers, Binghui Wang, Neil Zhenqiang Gong, Daji Qiao:
State Estimation via Inference on a Probabilistic Graphical Model - A Different Perspective. ISGT 2020: 1-5 - [c16]Nathan Inkawhich, Kevin J. Liang, Binghui Wang, Matthew Inkawhich, Lawrence Carin, Yiran Chen:
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability. NeurIPS 2020 - [c15]Jinyuan Jia, Binghui Wang, Xiaoyu Cao, Neil Zhenqiang Gong:
Certified Robustness of Community Detection against Adversarial Structural Perturbation via Randomized Smoothing. WWW 2020: 2718-2724 - [i21]Jinyuan Jia, Binghui Wang, Xiaoyu Cao, Neil Zhenqiang Gong:
Certified Robustness of Community Detection against Adversarial Structural Perturbation via Randomized Smoothing. CoRR abs/2002.03421 (2020) - [i20]Binghui Wang, Xiaoyu Cao, Jinyuan Jia, Neil Zhenqiang Gong:
On Certifying Robustness against Backdoor Attacks via Randomized Smoothing. CoRR abs/2002.11750 (2020) - [i19]Nathan Inkawhich, Kevin J. Liang, Binghui Wang, Matthew Inkawhich, Lawrence Carin, Yiran Chen:
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability. CoRR abs/2004.14861 (2020) - [i18]Zaixi Zhang, Jinyuan Jia, Binghui Wang, Neil Zhenqiang Gong:
Backdoor Attacks to Graph Neural Networks. CoRR abs/2006.11165 (2020) - [i17]Ang Li, Jingwei Sun, Binghui Wang, Lin Duan, Sicheng Li, Yiran Chen, Hai Li:
LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets. CoRR abs/2008.03371 (2020) - [i16]Binghui Wang, Jinyuan Jia, Xiaoyu Cao, Neil Zhenqiang Gong:
Certified Robustness of Graph Neural Networks against Adversarial Structural Perturbation. CoRR abs/2008.10715 (2020) - [i15]Houxiang Fan, Binghui Wang, Pan Zhou, Ang Li, Meng Pang, Zichuan Xu, Cai Fu, Hai Li, Yiran Chen:
Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs. CoRR abs/2009.00163 (2020) - [i14]Binghui Wang, Tianxiang Zhou, Minhua Lin, Pan Zhou, Ang Li, Meng Pang, Cai Fu, Hai Li, Yiran Chen:
Evasion Attacks to Graph Neural Networks via Influence Function. CoRR abs/2009.00203 (2020) - [i13]Jinyuan Jia, Binghui Wang, Neil Zhenqiang Gong:
Robust and Verifiable Information Embedding Attacks to Deep Neural Networks via Error-Correcting Codes. CoRR abs/2010.13751 (2020) - [i12]Jinyuan Jia, Binghui Wang, Xiaoyu Cao, Hongbin Liu, Neil Zhenqiang Gong:
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations. CoRR abs/2011.07633 (2020) - [i11]Binghui Wang, Ang Li, Hai Li, Yiran Chen:
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs. CoRR abs/2012.04187 (2020) - [i10]Jingwei Sun, Ang Li, Binghui Wang, Huanrui Yang, Hai Li, Yiran Chen:
Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective. CoRR abs/2012.06043 (2020) - [i9]Binghui Wang, Jinyuan Jia, Neil Zhenqiang Gong:
Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks. CoRR abs/2012.13085 (2020)
2010 – 2019
- 2019
- [j6]Meng Pang, Yiu-ming Cheung, Binghui Wang, Risheng Liu:
Robust heterogeneous discriminative analysis for face recognition with single sample per person. Pattern Recognit. 89: 91-107 (2019) - [j5]Binghui Wang, Jinyuan Jia, Le Zhang, Neil Zhenqiang Gong:
Structure-Based Sybil Detection in Social Networks via Local Rule-Based Propagation. IEEE Trans. Netw. Sci. Eng. 6(3): 523-537 (2019) - [c14]Binghui Wang, Neil Zhenqiang Gong:
Attacking Graph-based Classification via Manipulating the Graph Structure. CCS 2019: 2023-2040 - [c13]Binghui Wang, Jinyuan Jia, Neil Zhenqiang Gong:
Graph-based Security and Privacy Analytics via Collective Classification with Joint Weight Learning and Propagation. NDSS 2019 - [i8]Binghui Wang, Neil Zhenqiang Gong:
Attacking Graph-based Classification via Manipulating the Graph Structure. CoRR abs/1903.00553 (2019) - [i7]Jinyuan Jia, Xiaoyu Cao, Binghui Wang, Neil Zhenqiang Gong:
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing. CoRR abs/1912.09899 (2019) - 2018
- [c12]Peng Gao, Binghui Wang, Neil Zhenqiang Gong, Sanjeev R. Kulkarni, Kurt Thomas, Prateek Mittal:
SYBILFUSE: Combining Local Attributes with Global Structure to Perform Robust Sybil Detection. CNS 2018: 1-9 - [c11]Binghui Wang, Le Zhang, Neil Zhenqiang Gong:
SybilBlind: Detecting Fake Users in Online Social Networks Without Manual Labels. RAID 2018: 228-249 - [c10]Binghui Wang, Neil Zhenqiang Gong:
Stealing Hyperparameters in Machine Learning. IEEE Symposium on Security and Privacy 2018: 36-52 - [i6]Binghui Wang, Chuang Lin:
Robust Multi-subspace Analysis Using Novel Column L0-norm Constrained Matrix Factorization. CoRR abs/1801.09111 (2018) - [i5]Binghui Wang, Neil Zhenqiang Gong:
Stealing Hyperparameters in Machine Learning. CoRR abs/1802.05351 (2018) - [i4]Binghui Wang, Jinyuan Jia, Le Zhang, Neil Zhenqiang Gong:
Structure-based Sybil Detection in Social Networks via Local Rule-based Propagation. CoRR abs/1803.04321 (2018) - [i3]Peng Gao, Binghui Wang, Neil Zhenqiang Gong, Sanjeev R. Kulkarni, Kurt Thomas, Prateek Mittal:
SybilFuse: Combining Local Attributes with Global Structure to Perform Robust Sybil Detection. CoRR abs/1803.06772 (2018) - [i2]Binghui Wang, Le Zhang, Neil Zhenqiang Gong:
SybilBlind: Detecting Fake Users in Online Social Networks without Manual Labels. CoRR abs/1806.04853 (2018) - [i1]Binghui Wang, Jinyuan Jia, Neil Zhenqiang Gong:
Graph-based Security and Privacy Analytics via Collective Classification with Joint Weight Learning and Propagation. CoRR abs/1812.01661 (2018) - 2017
- [j4]Meng Pang, Binghui Wang, Yiu-Ming Cheung, Chuang Lin:
Discriminant Manifold Learning via Sparse Coding for Robust Feature Extraction. IEEE Access 5: 13978-13991 (2017) - [c9]Meng Pang, Yiu-ming Cheung, Binghui Wang, Risheng Liu:
Robust Heterogeneous Discriminative Analysis for Single Sample Per Person Face Recognition. CIKM 2017: 2251-2254 - [c8]Jinyuan Jia, Binghui Wang, Neil Zhenqiang Gong:
Random Walk Based Fake Account Detection in Online Social Networks. DSN 2017: 273-284 - [c7]Binghui Wang, Neil Zhenqiang Gong, Hao Fu:
GANG: Detecting Fraudulent Users in Online Social Networks via Guilt-by-Association on Directed Graphs. ICDM 2017: 465-474 - [c6]Binghui Wang, Le Zhang, Neil Zhenqiang Gong:
SybilSCAR: Sybil detection in online social networks via local rule based propagation. INFOCOM 2017: 1-9 - [c5]Jinyuan Jia, Binghui Wang, Le Zhang, Neil Zhenqiang Gong:
AttriInfer: Inferring User Attributes in Online Social Networks Using Markov Random Fields. WWW 2017: 1561-1569 - 2016
- [j3]Chuang Lin, Binghui Wang, Xin Fan, Yanchun Ma, Huiyun Liu:
Orthogonal enhanced linear discriminant analysis for face recognition. IET Biom. 5(2): 100-110 (2016) - [c4]Meng Pang, Binghui Wang, Xin Fan, Chuang Lin:
Discriminant Manifold Learning via Sparse Coding for Image Analysis. MMM (2) 2016: 244-255 - 2015
- [c3]Binghui Wang, Risheng Liu, Chuang Lin, Xin Fan:
Matrix Factorization with Column L0-Norm Constraint for Robust Multi-subspace Analysis. ICDM Workshops 2015: 1189-1195 - 2014
- [j2]Binghui Wang, Chuang Lin, Xue-Feng Zhao, Zhe-Ming Lu:
Neighbourhood sensitive preserving embedding for pattern classification. IET Image Process. 8(8): 489-497 (2014) - [j1]Binghui Wang, Chuang Lin, Xin Fan, Ning Jiang, Dario Farina:
Hierarchical Bayes based Adaptive Sparsity in Gaussian Mixture Model. Pattern Recognit. Lett. 49: 238-247 (2014) - 2013
- [c2]Binghui Wang, Meng Pang, Chuang Lin, Xin Fan:
Graph regularized non-negative matrix factorization with sparse coding. ChinaSIP 2013: 476-480 - 2012
- [c1]Huansheng Ning, Wei He, Sha Hu, Binghui Wang:
Space-Time Registration for Physical-Cyber World Mapping in Internet of Things. CIT 2012: 307-310
Coauthor Index
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