Multi-feature based score fusion method for fingerprint recognition accuracy boosting. - Qiongxiu Li; Changlong Jin; Weonjin Kim; Jungmin Kim; Shengzhe Li; Hakil Kim (APSIPA, 2016)

Fingerprint Liveness Detection Using CNN Features of Random Sample Patches. - Eunsoo Park; Weonjin Kim; Qiongxiu Li; Jungmin Kim; Hakil Kim (BIOSIG, 2016)

A Privacy-Preserving Asynchronous Averaging Algorithm based on Shamir's Secret Sharing. - Qiongxiu Li; Mads Græsbøll Christensen (EUSIPCO, 2019)

Privacy-Preserving Distributed Average Consensus based on Additive Secret Sharing. - Qiongxiu Li; Ignacio Cascudo; Mads Græsbøll Christensen (EUSIPCO, 2019)

Privacy-Preserving Distributed Graph Filtering. - Qiongxiu Li; Mario Coutino; Geert Leus; Mads Græsbøll Christensen (EUSIPCO, 2020)

Convex optimization-based Privacy-Preserving Distributed Least Squares via Subspace Perturbation. - Qiongxiu Li; Richard Heusdens; Mads Græsbøll Christensen (EUSIPCO, 2020)

Convex Optimisation-Based Privacy-Preserving Distributed Average Consensus in Wireless Sensor Networks. - Qiongxiu Li; Richard Heusdens; Mads Græsbøll Christensen (ICASSP, 2020)

Privacy-Preserving Distributed Optimization via Subspace Perturbation: A General Framework. - Qiongxiu Li; Richard Heusdens; Mads Græsbøll Christensen (IEEE Trans. Signal Process., 2020)

Privacy-Preserving Distributed Processing: Metrics, Bounds and Algorithms. - Qiongxiu Li; Jaron Skovsted Gundersen; Richard Heusdens; Mads Græsbøll Christensen (IEEE Trans. Inf. Forensics Secur., 2021)

Two for the price of one: communication efficient and privacy-preserving distributed average consensus using quantization. - Qiongxiu Li; Milan Lopuhaä-Zwakenberg; Richard Heusdens; Mads Græsbøll Christensen (EUSIPCO, 2022)

Privacy-Preserving Distributed Expectation Maximization for Gaussian Mixture Model Using Subspace Perturbation. - Qiongxiu Li; Jaron Skovsted Gundersen; Katrine Tjell; Rafal Wisniewski; Mads Græsbøll Christensen (ICASSP, 2022)

Communication efficient privacy-preserving distributed optimization using adaptive differential quantization. - Qiongxiu Li; Richard Heusdens; Mads Græsbøll Christensen (Signal Process., 2022)

On the Privacy Bound of Distributed Optimization and its Application in Federated Learning. - Qiongxiu Li; Milan Lopuhaä-Zwakenberg; Wenrui Yu; Richard Heusdens (EUSIPCO, 2024)

Privacy-Preserving Distributed Optimisation using Stochastic PDMM. - Sebastian O. Jordan; Qiongxiu Li; Richard Heusdens (ICASSP, 2024)

On the Privacy of Federated Clustering: a Cryptographic View. - Qiongxiu Li; Lixia Luo (ICASSP, 2024)

Topology-Dependent Privacy Bound for Decentralized Federated Learning. - Qiongxiu Li; Wenrui Yu; Changlong Ji; Richard Heusdens (ICASSP, 2024)

ADBM: Adversarial diffusion bridge model for reliable adversarial purification. - Xiao Li; Wenxuan Sun; Huanran Chen; Qiongxiu Li; Yining Liu; Yingzhe He; Jie Shi; Xiaolin Hu (CoRR, 2024)

An Intelligent Innovation Dataset on Scientific Research Outcomes. - Xinran Wu; Hui Zou; Yidan Xing; Jingjing Qu; Qiongxiu Li; Renxia Xue; Xiaoming Fu 001 (CoRR, 2024)

Perfect Gradient Inversion in Federated Learning: A New Paradigm from the Hidden Subset Sum Problem. - Qiongxiu Li; Lixia Luo; Agnese Gini; Changlong Ji; Zhanhao Hu; Xiao Li 028; Chengfang Fang; Jie Shi; Xiaolin Hu 001 (CoRR, 2024)

Faster-GCG: Efficient Discrete Optimization Jailbreak Attacks against Aligned Large Language Models. - Xiao Li; Zhuhong Li; Qiongxiu Li; Bingze Lee; Jinghao Cui; Xiaolin Hu (CoRR, 2024)

ProP: Efficient Backdoor Detection via Propagation Perturbation for Overparametrized Models. - Tao Ren; Qiongxiu Li (CoRR, 2024)

DeMem: Privacy-Enhanced Robust Adversarial Learning via De-Memorization. - Xiaoyu Luo; Qiongxiu Li (CoRR, 2024)

Adaptive Differentially Quantized Subspace Perturbation (ADQSP): A Unified Framework for Privacy-Preserving Distributed Average Consensus. - Qiongxiu Li; Jaron Skovsted Gundersen; Milan Lopuhaä-Zwakenberg; Richard Heusdens (IEEE Trans. Inf. Forensics Secur., 2024)

On the Privacy Effect of Data Enhancement via the Lens of Memorization. - Xiao Li 028; Qiongxiu Li; Zhanhao Hu; Xiaolin Hu 001 (IEEE Trans. Inf. Forensics Secur., 2024)

Re-Evaluating Privacy in Centralized and Decentralized Learning: An Information-Theoretical and Empirical Study. - Changlong Ji; Richard Heusdens; Stephane Maag; Qiongxiu Li (ICASSP, 2025)

Privacy-Preserving Distributed Maximum Consensus Without Accuracy Loss. - Wenrui Yu; Richard Heusdens; Jun Pang 001; Qiongxiu Li (ICASSP, 2025)

ADBM: Adversarial Diffusion Bridge Model for Reliable Adversarial Purification. - Xiao Li; Wenxuan Sun; Huanran Chen; Qiongxiu Li; Yingzhe He; Jie Shi; Xiaolin Hu (ICLR, 2025)

Large Language Models are Easily Confused: A Quantitative Metric, Security Implications and Typological Analysis. - Yiyi Chen 002; Qiongxiu Li; Russa Biswas; Johannes Bjerva (NAACL (Findings), 2025)

Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization. - Wenrui Yu; Qiongxiu Li; Milan Lopuhaä-Zwakenberg; Mads Græsbøll Christensen; Richard Heusdens (IEEE Trans. Inf. Forensics Secur., 2025)

Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond. - Qiongxiu Li; Xiaoyu Luo; Yiyi Chen 002; Johannes Bjerva (CoRR, 2025)

From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges. - Qiongxiu Li; Wenrui Yu; Yufei Xia; Jun Pang 001 (CoRR, 2025)

Byzantine-Resilient Federated Learning via Distributed Optimization. - Yufei Xia; Wenrui Yu; Qiongxiu Li (CoRR, 2025)

Shared Path: Unraveling Memorization in Multilingual LLMs through Language Similarities. - Xiaoyu Luo; Yiyi Chen 002; Johannes Bjerva; Qiongxiu Li (CoRR, 2025)

LAGO: Few-shot Crosslingual Embedding Inversion Attacks via Language Similarity-Aware Graph Optimization. - Wenrui Yu; Yiyi Chen 002; Johannes Bjerva; Sokol Kosta; Qiongxiu Li (CoRR, 2025)