Q-ShiftDP: A Differentially Private Parameter-Shift Rule for Quantum Machine Learning
Authors: Hoang M. Ngo, Nhat Hoang-Xuan, Quan Nguyen, Nguyen Do, Incheol Shin, My T. Thai | Published: 2026-02-03
量子化とプライバシー
Guaranteeing Privacy in Hybrid Quantum Learning through Theoretical Mechanisms
Authors: Hoang M. Ngo, Tre' R. Jeter, Incheol Shin, Wanli Xing, Tamer Kahveci, My T. Thai | Published: 2026-02-02
Adversarial Contrastive Learning for LLM Quantization Attacks
Authors: Dinghong Song, Zhiwei Xu, Hai Wan, Xibin Zhao, Pengfei Su, Dong Li | Published: 2026-01-06
Membership Inference Risks in Quantized Models: A Theoretical and Empirical Study
Authors: Eric Aubinais, Philippe Formont, Pablo Piantanida, Elisabeth Gassiat | Published: 2025-02-10
Promoting Data and Model Privacy in Federated Learning through Quantized LoRA
Authors: JianHao Zhu, Changze Lv, Xiaohua Wang, Muling Wu, Wenhao Liu, Tianlong Li, Zixuan Ling, Cenyuan Zhang, Xiaoqing Zheng, Xuanjing Huang | Published: 2024-06-16
The Effect of Quantization in Federated Learning: A Rényi Differential Privacy Perspective
Authors: Tianqu Kang, Lumin Liu, Hengtao He, Jun Zhang, S. H. Song, Khaled B. Letaief | Published: 2024-05-16
RQP-SGD: Differential Private Machine Learning through Noisy SGD and Randomized Quantization
Authors: Ce Feng, Parv Venkitasubramaniam | Published: 2024-02-09
Quantization-aware Neural Architectural Search for Intrusion Detection
Authors: Rabin Yu Acharya, Laurens Le Jeune, Nele Mentens, Fatemeh Ganji, Domenic Forte | Published: 2023-11-07 | Updated: 2024-03-02
Improving Robustness Against Adversarial Attacks with Deeply Quantized Neural Networks
Authors: Ferheen Ayaz, Idris Zakariyya, José Cano, Sye Loong Keoh, Jeremy Singer, Danilo Pau, Mounia Kharbouche-Harrari | Published: 2023-04-25
QuMoS: A Framework for Preserving Security of Quantum Machine Learning Model
Authors: Zhepeng Wang, Jinyang Li, Zhirui Hu, Blake Gage, Elizabeth Iwasawa, Weiwen Jiang | Published: 2023-04-23 | Updated: 2023-10-13