Federated Learning in Practice: Reflections and Projections
Authors: Katharine Daly, Hubert Eichner, Peter Kairouz, H. Brendan McMahan, Daniel Ramage, Zheng Xu | Published: 2024-10-11
プライバシー保護手法
PILLAR: an AI-Powered Privacy Threat Modeling Tool
Authors: Majid Mollaeefar, Andrea Bissoli, Silvio Ranise | Published: 2024-10-11
Privately Learning from Graphs with Applications in Fine-tuning Large Language Models
Authors: Haoteng Yin, Rongzhe Wei, Eli Chien, Pan Li | Published: 2024-10-10
Near Exact Privacy Amplification for Matrix Mechanisms
Authors: Christopher A. Choquette-Choo, Arun Ganesh, Saminul Haque, Thomas Steinke, Abhradeep Thakurta | Published: 2024-10-08 | Updated: 2025-03-20
KnowledgeSG: Privacy-Preserving Synthetic Text Generation with Knowledge Distillation from Server
Authors: Wenhao Wang, Xiaoyu Liang, Rui Ye, Jingyi Chai, Siheng Chen, Yanfeng Wang | Published: 2024-10-08 | Updated: 2024-10-10
A Comprehensive Study on GDPR-Oriented Analysis of Privacy Policies: Taxonomy, Corpus and GDPR Concept Classifiers
Authors: Peng Tang, Xin Li, Yuxin Chen, Weidong Qiu, Haochen Mei, Allison Holmes, Fenghua Li, Shujun Li | Published: 2024-10-07
Adaptively Private Next-Token Prediction of Large Language Models
Authors: James Flemings, Meisam Razaviyayn, Murali Annavaram | Published: 2024-10-02
Scalable Differential Privacy Mechanisms for Real-Time Machine Learning Applications
Authors: Jessica Smith, David Williams, Emily Brown | Published: 2024-09-16
Federated Learning with Quantum Computing and Fully Homomorphic Encryption: A Novel Computing Paradigm Shift in Privacy-Preserving ML
Authors: Siddhant Dutta, Pavana P Karanth, Pedro Maciel Xavier, Iago Leal de Freitas, Nouhaila Innan, Sadok Ben Yahia, Muhammad Shafique, David E. Bernal Neira | Published: 2024-09-14 | Updated: 2024-10-12
Exploring User-level Gradient Inversion with a Diffusion Prior
Authors: Zhuohang Li, Andrew Lowy, Jing Liu, Toshiaki Koike-Akino, Bradley Malin, Kieran Parsons, Ye Wang | Published: 2024-09-11