Gaussian Iteration: A Novel Way to Collaborative Filtering. - Xiaochun Li; Fangqi Li 001; Ying Guo 004; Jinchao Huang 001 (ICIC (3), 2016)

Probabilistic Model of Object Detection Based on Convolutional Neural Network. - Fangqi Li 001; Xu-Die Ren; Hao-Nan Guo (CSPS, 2017)

An Efficient Classification Method of Uncertain Data with Sampling. - Jinchao Huang 001; Yulin Li; Kaiyue Qi; Fangqi Li 001 (CSPS (2), 2018)

A Multi-view Deep Learning Approach for Detecting Threats on 3D Human Body. - Zhicong Yan; Shuai Feng; Fangqi Li 001; Zhengwu Xu; Shenghong Li 001 (CSPS (3), 2018)

Lip Segmentation with Muti-scale Features Based on Fully Convolution Network. - Zhen Ju; Xiang Lin; Fangqi Li 001; Shilin Wang (DSC, 2018)

Laplace Exponential Family PCA. - Fangqi Li 001; Xudie Ren (ICIC (1), 2018)

Maximizing Influence on Social Networks with Conjugate Learning Automata. - Chong Di 001; Fangqi Li 001; Kaiyue Qi; Shenghong Li 001 (GLOBECOM, 2019)

A Novel Framework for Learning Automata: A Statistical Hypothesis Testing Approach. - Chong Di 001; Shenghong Li 001; Fangqi Li 001; Kaiyue Qi (IEEE Access, 2019)

A Bayesian Possibilistic C-Means clustering approach for cervical cancer screening. - Fangqi Li 001; Shi-Lin Wang; Gongshen Liu (Inf. Sci., 2019)

Gaussian Process Bandits for Online Influence Maximization. - Wenwen Xia; Fangqi Li 001; Shenghong Li 001 (ICDM (Workshops), 2020)

On the Submodularity of Diffusion Models: Equivalent Conditions and Applications. - Fangqi Li 001; Chong Di 001; Wenwen Xia (CoRR, 2020)

The Electromagnetic Balance Game: A Probabilistic Perspective. - Fangqi Li 001 (CoRR, 2020)

Solving the Three-Player-Game. - Fangqi Li 001 (CoRR, 2020)

Influence Maximization on Dynamic Social Networks with Conjugate Learning Automata. - Fangqi Li 001; Chong Di 001; Shenghong Li 001 (CoRR, 2020)

Evaluation and Comparison of Diffusion Models with Motif Features. - Fangqi Li 001 (CoRR, 2020)

Sensor Deployment for Wireless Sensor Networks: A Conjugate Learning Automata-Based Energy-Efficient Approach. - Chong Di 001; Fangqi Li 001; Shenghong Li 001 (IEEE Wirel. Commun., 2020)

Protecting Deep Cerebrospinal Fluid Cell Image Processing Models with Backdoor and Semi-Distillation. - Fang-Qi Li 001; Shi-Lin Wang; Zhen-Hai Wang (DICTA, 2021)

Persistent Watermark For Image Classification Neural Networks By Penetrating The Autoencoder. - Fang-Qi Li 001; Shi-Lin Wang (ICIP, 2021)

Bayesian inference based learning automaton scheme in Q-model environments. - Chong Di 001; Fangqi Li 001; Shenghong Li 001; Jianwei Tian (Appl. Intell., 2021)

Secure Watermark for Deep Neural Networks with Multi-task Learning. - Fangqi Li 001; Shilin Wang (CoRR, 2021)

Towards Practical Watermark for Deep Neural Networks in Federated Learning. - Fangqi Li 001; Shi-Lin Wang (CoRR, 2021)

Regulating Ownership Verification for Deep Neural Networks: Scenarios, Protocols, and Prospects. - Fangqi Li 001; Shi-Lin Wang; Alan Wee-Chung Liew (CoRR, 2021)

FastCover: An Unsupervised Learning Framework for Multi-Hop Influence Maximization in Social Networks. - Runbo Ni; Xueyan Li; Fangqi Li 001; Xiaofeng Gao 001; Guihai Chen (CoRR, 2021)

Large-Scale Malicious Software Classification With Fuzzified Features and Boosted Fuzzy Random Forest. - Fang-Qi Li 001; Shi-Lin Wang; Alan Wee-Chung Liew; Weiping Ding 001; Gongshen Liu (IEEE Trans. Fuzzy Syst., 2021)

An Efficient Parameter-Free Learning Automaton Scheme. - Chong Di 001; Qilian Liang; Fangqi Li 001; Shenghong Li 001; Fucai Luo (IEEE Trans. Neural Networks Learn. Syst., 2021)

Leveraging Multi-task Learning for Umambiguous and Flexible Deep Neural Network Watermarking. - Fangqi Li 001; Lei Yang 062; Shilin Wang; Alan Wee-Chung Liew (SafeAI@AAAI, 2022)

Fostering The Robustness Of White-Box Deep Neural Network Watermarks By Neuron Alignment. - Fang-Qi Li 001; Shi-Lin Wang; Yun Zhu (ICASSP, 2022)

Watermarking Protocol for Deep Neural Network Ownership Regulation in Federated Learning. - Fang-Qi Li 001; Shi-Lin Wang; Alan Wee-Chung Liew (ICME Workshops, 2022)

Knowledge-Free Black-Box Watermark and Ownership Proof for Image Classification Neural Networks. - Fangqi Li 001; Shilin Wang (CoRR, 2022)

Reduce Communication Costs and Preserve Privacy: Prompt Tuning Method in Federated Learning. - Haodong Zhao; Wei Du; Fangqi Li 001; Peixuan Li; Gongshen Liu (CoRR, 2022)

Solving the Capsulation Attack against Backdoor-based Deep Neural Network Watermarks by Reversing Triggers. - Fangqi Li 001; Shilin Wang; Yun Zhu (CoRR, 2022)

Online Intrusion Detection for Internet of Things Systems With Full Bayesian Possibilistic Clustering and Ensembled Fuzzy Classifiers. - Fang-Qi Li 001; Ruijie Zhao 001; Shi-Lin Wang; Li-Bo Chen 001; Alan Wee-Chung Liew; Weiping Ding 001 (IEEE Trans. Fuzzy Syst., 2022)

PLMmark: A Secure and Robust Black-Box Watermarking Framework for Pre-trained Language Models. - Peixuan Li; Pengzhou Cheng; Fangqi Li 001; Wei Du; Haodong Zhao; Gongshen Liu (AAAI, 2023)

Measure and Countermeasure of the Capsulation Attack Against Backdoor-Based Deep Neural Network Watermarks. - Fang-Qi Li 001; Shi-Lin Wang; Yun Zhu (ICASSP, 2023)

FedPrompt: Communication-Efficient and Privacy-Preserving Prompt Tuning in Federated Learning. - Haodong Zhao; Wei Du; Fangqi Li 001; Peixuan Li; Gongshen Liu (ICASSP, 2023)

Improve Deep Forest with Learnable Layerwise Augmentation Policy Schedule. - Hongyu Zhu 004; Sichu Liang; Wentao Hu; Fang-Qi Li 001; Yali Yuan; Shi-Lin Wang; Guang Cheng 001 (CoRR, 2023)

Measuring and Understanding Crowdturfing in the App Store. - Qinyu Hu; Xiaomei Zhang; Fangqi Li 001; Zhushou Tang; Shilin Wang (Inf., 2023)

Linear Functionality Equivalence Attack Against Deep Neural Network Watermarks and a Defense Method by Neuron Mapping. - Fang-Qi Li 001; Shi-Lin Wang; Alan Wee-Chung Liew (IEEE Trans. Inf. Forensics Secur., 2023)

Learning automata-accelerated greedy algorithms for stochastic submodular maximization. - Chong Di 001; Fangqi Li 001; Pengyao Xu; Ying Guo 004; Chao Chen 009; Minglei Shu (Knowl. Based Syst., 2023)

Revisiting the Information Capacity of Neural Network Watermarks: Upper Bound Estimation and Beyond. - Fangqi Li 001; Haodong Zhao; Wei Du; Shilin Wang (AAAI, 2024)

R-Judge: Benchmarking Safety Risk Awareness for LLM Agents. - Tongxin Yuan; Zhiwei He 002; Lingzhong Dong; Yiming Wang 011; Ruijie Zhao 001; Tian Xia; Lizhen Xu; Binglin Zhou; Fangqi Li 001; Zhuosheng Zhang 001; Rui Wang 015; Gongshen Liu (EMNLP (Findings), 2024)

Improve Deep Forest with Learnable Layerwise Augmentation Policy Schedules. - Hongyu Zhu 004; Sichu Liang; Wentao Hu; Fang-Qi Li 001; Yali Yuan; Shi-Lin Wang; Guang Cheng 001 (ICASSP, 2024)

Data-Free Watermark for Deep Neural Networks by Truncated Adversarial Distillation. - Chao-Bo Yan; Fang-Qi Li 001; Shi-Lin Wang (ICASSP, 2024)

Reliable Model Watermarking: Defending against Theft without Compromising on Evasion. - Hongyu Zhu 004; Sichu Liang; Wentao Hu; Fangqi Li 001; Ju Jia; Shi-Lin Wang (ACM Multimedia, 2024)

Efficient and Effective Model Extraction. - Hongyu Zhu 004; Wentao Hu; Sichu Liang; Fangqi Li 001; Wenwen Wang; Shilin Wang (CoRR, 2024)

NSmark: Null Space Based Black-box Watermarking Defense Framework for Pre-trained Language Models. - Haodong Zhao; Jinming Hu; Peixuan Li; Fangqi Li 001; Jinrui Sha; Peixuan Chen; Zhuosheng Zhang 001; Gongshen Liu (CoRR, 2024)

PromptLA: Towards Integrity Verification of Black-box Text-to-Image Diffusion Models. - Zhuomeng Zhang; Fangqi Li 001; Chong Di 001; Shilin Wang (CoRR, 2024)

A Novel Self-Supervised Framework Based on Masked Autoencoder for Traffic Classification. - Ruijie Zhao 001; Mingwei Zhan; Xianwen Deng; Fangqi Li 001; Yanhao Wang; Yijun Wang; Guan Gui 001; Zhi Xue (IEEE/ACM Trans. Netw., 2024)

Rethinking the Fragility and Robustness of Fingerprints of Deep Neural Networks. - Fangqi Li 001; Shilin Wang; Lei Yang 062 (ICASSP, 2025)