:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Ma, Xirong
Format:	Preprint
Published:	2023
Subjects:	Cryptography and Security Machine Learning
Online Access:	https://arxiv.org/abs/2305.17341
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Efficient Privacy-Preserving KAN Inference Using Homomorphic Encryption
by: Lai, Zhizheng, et al.
Published: (2024)

Secure Sparse Matrix Multiplications and their Applications to Privacy-Preserving Machine Learning
by: Damie, Marc, et al.
Published: (2025)

Efficient Privacy-Preserving Sparse Matrix-Vector Multiplication Using Homomorphic Encryption
by: Gao, Yang, et al.
Published: (2026)

Privacy-Preserving Federated Learning via Homomorphic Adversarial Networks
by: Dong, Wenhan, et al.
Published: (2024)

FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System
by: Jin, Weizhao, et al.
Published: (2023)

GuardML: Efficient Privacy-Preserving Machine Learning Services Through Hybrid Homomorphic Encryption
by: Frimpong, Eugene, et al.
Published: (2024)

Comparison of Fully Homomorphic Encryption and Garbled Circuit Techniques in Privacy-Preserving Machine Learning Inference
by: Cheerla, Kalyan, et al.
Published: (2025)

Privacy-Preserving Graph-Based Machine Learning with Fully Homomorphic Encryption for Collaborative Anti-Money Laundering
by: Effendi, Fabrianne, et al.
Published: (2024)

Efficient Privacy-Preserving Recommendation on Sparse Data using Fully Homomorphic Encryption
by: Chowdhury, Moontaha Nishat, et al.
Published: (2025)

HETAL: Efficient Privacy-preserving Transfer Learning with Homomorphic Encryption
by: Lee, Seewoo, et al.
Published: (2024)

Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM
by: Xie, Chulin, et al.
Published: (2022)

A Novel Review of Stability Techniques for Improved Privacy-Preserving Machine Learning
by: DuPlessie, Coleman, et al.
Published: (2024)

Privacy Amplification for Matrix Mechanisms
by: Choquette-Choo, Christopher A., et al.
Published: (2023)

A Privacy-Centric Approach: Scalable and Secure Federated Learning Enabled by Hybrid Homomorphic Encryption
by: Nguyen, Khoa, et al.
Published: (2025)

CHEHAB RL: Learning to Optimize Fully Homomorphic Encryption Computations
by: Sefsaf, Bilel, et al.
Published: (2026)

Data Privacy Preservation on the Internet of Things
by: Sen, Jaydip, et al.
Published: (2023)

Agentic Privacy-Preserving Machine Learning
by: Zhang, Mengyu, et al.
Published: (2025)

Preserving Privacy and Security in Federated Learning
by: Nguyen, Truc, et al.
Published: (2022)

SafeSynthDP: Leveraging Large Language Models for Privacy-Preserving Synthetic Data Generation Using Differential Privacy
by: Nahid, Md Mahadi Hasan, et al.
Published: (2024)

Revisiting ML Training under Fully Homomorphic Encryption: Convergence Guarantees, Differential Privacy, and Efficient Algorithms
by: Zhou, Yvonne, et al.
Published: (2026)

Privacy-Preserving Inference for Quantized BERT Models
by: Lu, Tianpei, et al.
Published: (2025)

Privacy Preserving Reinforcement Learning for Population Processes
by: Yang-Zhao, Samuel, et al.
Published: (2024)

Privacy-Preserving Vertical K-Means Clustering
by: Mazzone, Federico, et al.
Published: (2025)

Privacy-Preserving Fair Synthetic Tabular Data
by: Sarmin, Fatima J., et al.
Published: (2025)

Privacy Preservation through Practical Machine Unlearning
by: Dilworth, Robert
Published: (2025)

Privacy-Preserving Hierarchical Model-Distributed Inference
by: Dehkordi, Fatemeh Jafarian, et al.
Published: (2024)

Towards Privacy-Preserving Medical Imaging: Federated Learning with Differential Privacy and Secure Aggregation Using a Modified ResNet Architecture
by: Fares, Mohamad Haj, et al.
Published: (2024)

PRISM: Privacy-preserving Inference System with Homomorphic Encryption and Modular Activation
by: Elkhatib, Zeinab, et al.
Published: (2025)

Traveling Salesman-Based Token Ordering Improves Stability in Homomorphically Encrypted Language Models
by: Rho, Donghwan, et al.
Published: (2025)

Hawk: Accurate and Fast Privacy-Preserving Machine Learning Using Secure Lookup Table Computation
by: Saleem, Hamza, et al.
Published: (2024)

CENTAUR: Bridging the Impossible Trinity of Privacy, Efficiency, and Performance in Privacy-Preserving Transformer Inference
by: Luo, Jinglong, et al.
Published: (2024)

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy
by: Li, Xiang, et al.
Published: (2025)

Optimizing Privacy-Preserving Primitives to Support LLM-Scale Applications
by: Jandali, Yaman, et al.
Published: (2025)

Preserving Node-level Privacy in Graph Neural Networks
by: Xiang, Zihang, et al.
Published: (2023)

Privacy-Preserving 3-Layer Neural Network Training
by: Chiang, John
Published: (2023)

Privacy-Preserving Optimal Parameter Selection for Collaborative Clustering
by: Ghasemian, Maryam, et al.
Published: (2024)

Privacy-Preserving Verifiable Neural Network Inference Service
by: Riasi, Arman, et al.
Published: (2024)

Privacy-Preserving Generative Models: A Comprehensive Survey
by: Padariya, Debalina, et al.
Published: (2025)

Automated Privacy-Preserving Techniques via Meta-Learning
by: Carvalho, Tânia, et al.
Published: (2024)

Preserving Expert-Level Privacy in Offline Reinforcement Learning
by: Sharma, Navodita, et al.
Published: (2024)