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ORCIDFangqi Li 0001
Person information
- affiliation: Shanghai Jiao Tong University, School of Electronic Information and Electrical Engineering, Shanghai, China
Other persons with the same name
- Fangqi Li (aka: Fang-Qi Li) — disambiguation page
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Journal Articles
- 2024
[j11]Ruijie Zhao
, Mingwei Zhan, Xianwen Deng, Fangqi Li, Yanhao Wang, Yijun Wang, Guan Gui, Zhi Xue:
A Novel Self-Supervised Framework Based on Masked Autoencoder for Traffic Classification. IEEE/ACM Trans. Netw. 32(3): 2012-2025 (2024)- 2023
- [j10]Qinyu Hu, Xiaomei Zhang, Fangqi Li, Zhushou Tang, Shilin Wang:
Measuring and Understanding Crowdturfing in the App Store. Inf. 14(7): 393 (2023) - [j9]Chong Di, Fangqi Li, Pengyao Xu, Ying Guo, Chao Chen, Minglei Shu:
Learning automata-accelerated greedy algorithms for stochastic submodular maximization. Knowl. Based Syst. 282: 111118 (2023) - [j8]Fang-Qi Li, Shi-Lin Wang, Alan Wee-Chung Liew:
Linear Functionality Equivalence Attack Against Deep Neural Network Watermarks and a Defense Method by Neuron Mapping. IEEE Trans. Inf. Forensics Secur. 18: 1963-1977 (2023) - 2022
- [j7]Fang-Qi Li, Ruijie Zhao, Shi-Lin Wang, Li-Bo Chen, Alan Wee-Chung Liew, Weiping Ding:
Online Intrusion Detection for Internet of Things Systems With Full Bayesian Possibilistic Clustering and Ensembled Fuzzy Classifiers. IEEE Trans. Fuzzy Syst. 30(11): 4605-4617 (2022) - 2021
- [j6]Chong Di, Fangqi Li, Shenghong Li, Jianwei Tian:
Bayesian inference based learning automaton scheme in Q-model environments. Appl. Intell. 51(10): 7453-7468 (2021) - [j5]Fang-Qi Li, Shi-Lin Wang, Alan Wee-Chung Liew, Weiping Ding, Gongshen Liu:
Large-Scale Malicious Software Classification With Fuzzified Features and Boosted Fuzzy Random Forest. IEEE Trans. Fuzzy Syst. 29(11): 3205-3218 (2021) - [j4]Chong Di, Qilian Liang, Fangqi Li, Shenghong Li, Fucai Luo:
An Efficient Parameter-Free Learning Automaton Scheme. IEEE Trans. Neural Networks Learn. Syst. 32(11): 4849-4863 (2021) - 2020
- [j3]Chong Di, Fangqi Li, Shenghong Li:
Sensor Deployment for Wireless Sensor Networks: A Conjugate Learning Automata-Based Energy-Efficient Approach. IEEE Wirel. Commun. 27(5): 80-87 (2020) - 2019
- [j2]Chong Di, Shenghong Li, Fangqi Li, Kaiyue Qi:
A Novel Framework for Learning Automata: A Statistical Hypothesis Testing Approach. IEEE Access 7: 27911-27922 (2019) - [j1]Fangqi Li, Shi-Lin Wang, Gongshen Liu:
A Bayesian Possibilistic C-Means clustering approach for cervical cancer screening. Inf. Sci. 501: 495-510 (2019)
Conference and Workshop Papers
- 2024
- [c19]Fangqi Li, Haodong Zhao, Wei Du, Shilin Wang:
Revisiting the Information Capacity of Neural Network Watermarks: Upper Bound Estimation and Beyond. AAAI 2024: 21331-21339 - [c18]Chao-Bo Yan, Fang-Qi Li, Shi-Lin Wang:
Data-Free Watermark for Deep Neural Networks by Truncated Adversarial Distillation. ICASSP 2024: 4480-4484 - [c17]Hongyu Zhu, Sichu Liang, Wentao Hu, Fang-Qi Li, Yali Yuan, Shi-Lin Wang, Guang Cheng:
Improve Deep Forest with Learnable Layerwise Augmentation Policy Schedules. ICASSP 2024: 6660-6664 - 2023
- [c16]Peixuan Li, Pengzhou Cheng, Fangqi Li, Wei Du, Haodong Zhao, Gongshen Liu:
PLMmark: A Secure and Robust Black-Box Watermarking Framework for Pre-trained Language Models. AAAI 2023: 14991-14999 - [c15]Fang-Qi Li, Shi-Lin Wang, Yun Zhu:
Measure and Countermeasure of the Capsulation Attack Against Backdoor-Based Deep Neural Network Watermarks. ICASSP 2023: 1-5 - [c14]Haodong Zhao, Wei Du, Fangqi Li, Peixuan Li, Gongshen Liu:
FedPrompt: Communication-Efficient and Privacy-Preserving Prompt Tuning in Federated Learning. ICASSP 2023: 1-5 - 2022
- [c13]Fangqi Li, Lei Yang, Shilin Wang, Alan Wee-Chung Liew:
Leveraging Multi-task Learning for Umambiguous and Flexible Deep Neural Network Watermarking. SafeAI@AAAI 2022 - [c12]Fang-Qi Li, Shi-Lin Wang, Yun Zhu:
Fostering The Robustness Of White-Box Deep Neural Network Watermarks By Neuron Alignment. ICASSP 2022: 3049-3053 - [c11]Fang-Qi Li, Shi-Lin Wang, Alan Wee-Chung Liew:
Watermarking Protocol for Deep Neural Network Ownership Regulation in Federated Learning. ICME Workshops 2022: 1-4 - 2021
- [c10]Fang-Qi Li, Shi-Lin Wang, Zhen-Hai Wang:
Protecting Deep Cerebrospinal Fluid Cell Image Processing Models with Backdoor and Semi-Distillation. DICTA 2021: 1-7 - [c9]Fang-Qi Li, Shi-Lin Wang:
Persistent Watermark For Image Classification Neural Networks By Penetrating The Autoencoder. ICIP 2021: 3063-3067 - 2020
- [c8]Wenwen Xia, Fangqi Li, Shenghong Li:
Gaussian Process Bandits for Online Influence Maximization. ICDM (Workshops) 2020: 106-113 - 2019
- [c7]Chong Di, Fangqi Li, Kaiyue Qi, Shenghong Li:
Maximizing Influence on Social Networks with Conjugate Learning Automata. GLOBECOM 2019: 1-6 - 2018
- [c6]Zhicong Yan, Shuai Feng, Fangqi Li, Zhengwu Xu, Shenghong Li:
A Multi-view Deep Learning Approach for Detecting Threats on 3D Human Body. CSPS (3) 2018: 286-294 - [c5]Jinchao Huang, Yulin Li, Kaiyue Qi, Fangqi Li:
An Efficient Classification Method of Uncertain Data with Sampling. CSPS (2) 2018: 345-353 - [c4]Zhen Ju, Xiang Lin, Fangqi Li, Shilin Wang:
Lip Segmentation with Muti-scale Features Based on Fully Convolution Network. DSC 2018: 365-370 - [c3]Fangqi Li, Xudie Ren:
Laplace Exponential Family PCA. ICIC (1) 2018: 322-333 - 2017
- [c2]Fangqi Li, Xu-Die Ren, Hao-Nan Guo:
Probabilistic Model of Object Detection Based on Convolutional Neural Network. CSPS 2017: 2059-2066 - 2016
- [c1]Xiaochun Li, Fangqi Li, Ying Guo, Jinchao Huang:
Gaussian Iteration: A Novel Way to Collaborative Filtering. ICIC (3) 2016: 260-270
Informal and Other Publications
- 2024
- [i19]Tongxin Yuan, Zhiwei He, Lingzhong Dong, Yiming Wang, Ruijie Zhao, Tian Xia, Lizhen Xu, Binglin Zhou, Fangqi Li, Zhuosheng Zhang, Rui Wang, Gongshen Liu:
R-Judge: Benchmarking Safety Risk Awareness for LLM Agents. CoRR abs/2401.10019 (2024) - [i18]Fangqi Li, Haodong Zhao, Wei Du, Shilin Wang:
Revisiting the Information Capacity of Neural Network Watermarks: Upper Bound Estimation and Beyond. CoRR abs/2402.12720 (2024) - [i17]Hongyu Zhu, Sichu Liang, Wentao Hu, Fangqi Li, Ju Jia, Shilin Wang:
Reliable Model Watermarking: Defending Against Theft without Compromising on Evasion. CoRR abs/2404.13518 (2024) - [i16]Hongyu Zhu, Wentao Hu, Sichu Liang, Fangqi Li, Wenwen Wang, Shilin Wang:
Efficient and Effective Model Extraction. CoRR abs/2409.14122 (2024) - 2023
- [i15]Hongyu Zhu, Sichu Liang, Wentao Hu, Fang-Qi Li, Yali Yuan, Shi-Lin Wang, Guang Cheng:
Improve Deep Forest with Learnable Layerwise Augmentation Policy Schedule. CoRR abs/2309.09030 (2023) - 2022
- [i14]Fangqi Li, Shilin Wang:
Knowledge-Free Black-Box Watermark and Ownership Proof for Image Classification Neural Networks. CoRR abs/2204.04522 (2022) - [i13]Haodong Zhao, Wei Du, Fangqi Li, Peixuan Li, Gongshen Liu:
Reduce Communication Costs and Preserve Privacy: Prompt Tuning Method in Federated Learning. CoRR abs/2208.12268 (2022) - [i12]Fangqi Li, Shilin Wang, Yun Zhu:
Solving the Capsulation Attack against Backdoor-based Deep Neural Network Watermarks by Reversing Triggers. CoRR abs/2208.14127 (2022) - 2021
- [i11]Fangqi Li, Shilin Wang:
Secure Watermark for Deep Neural Networks with Multi-task Learning. CoRR abs/2103.10021 (2021) - [i10]Fangqi Li, Shi-Lin Wang:
Towards Practical Watermark for Deep Neural Networks in Federated Learning. CoRR abs/2105.03167 (2021) - [i9]Fangqi Li, Shi-Lin Wang, Alan Wee-Chung Liew:
Regulating Ownership Verification for Deep Neural Networks: Scenarios, Protocols, and Prospects. CoRR abs/2108.09065 (2021) - [i8]Runbo Ni, Xueyan Li, Fangqi Li, Xiaofeng Gao, Guihai Chen:
FastCover: An Unsupervised Learning Framework for Multi-Hop Influence Maximization in Social Networks. CoRR abs/2111.00463 (2021) - [i7]Fang-Qi Li, Shi-Lin Wang, Yun Zhu:
Fostering the Robustness of White-Box Deep Neural Network Watermarks by Neuron Alignment. CoRR abs/2112.14108 (2021) - 2020
- [i6]Fangqi Li, Chong Di, Wenwen Xia:
On the Submodularity of Diffusion Models: Equivalent Conditions and Applications. CoRR abs/2002.00845 (2020) - [i5]Fangqi Li:
The Electromagnetic Balance Game: A Probabilistic Perspective. CoRR abs/2007.10735 (2020) - [i4]Fangqi Li:
Solving the Three-Player-Game. CoRR abs/2008.09796 (2020) - [i3]Fangqi Li, Chong Di, Shenghong Li:
Influence Maximization on Dynamic Social Networks with Conjugate Learning Automata. CoRR abs/2010.10950 (2020) - [i2]Fangqi Li:
Evaluation and Comparison of Diffusion Models with Motif Features. CoRR abs/2012.06816 (2020) - 2018
- [i1]Fangqi Li, Xu-Die Ren, Hao-Nan Guo:
Probabilistic Model of Object Detection Based on Convolutional Neural Network. CoRR abs/1808.08272 (2018)
Coauthor Index
aka: Shilin Wang
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