A Novel Review of Stability Techniques for Improved Privacy-Preserving Machine Learning
Fuente:
arXiv
Saved in:
| Main Authors: | DuPlessie, Coleman, Gao, Aidan |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Agentic Privacy-Preserving Machine Learning
by: Zhang, Mengyu, et al.
Published: (2025)
by: Zhang, Mengyu, et al.
Published: (2025)
Automated Privacy-Preserving Techniques via Meta-Learning
by: Carvalho, Tânia, et al.
Published: (2024)
by: Carvalho, Tânia, 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)
by: Cheerla, Kalyan, et al.
Published: (2025)
Secure Sparse Matrix Multiplications and their Applications to Privacy-Preserving Machine Learning
by: Damie, Marc, et al.
Published: (2025)
by: Damie, Marc, et al.
Published: (2025)
Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM
by: Xie, Chulin, et al.
Published: (2022)
by: Xie, Chulin, et al.
Published: (2022)
Privacy Preservation through Practical Machine Unlearning
by: Dilworth, Robert
Published: (2025)
by: Dilworth, Robert
Published: (2025)
Privacy-Preserving Machine Learning for IoT: A Cross-Paradigm Survey and Future Roadmap
by: Zaman, Zakia, et al.
Published: (2026)
by: Zaman, Zakia, et al.
Published: (2026)
The Normal Distributions Indistinguishability Spectrum and its Application to Privacy-Preserving Machine Learning
by: Wei, Yu, et al.
Published: (2023)
by: Wei, Yu, et al.
Published: (2023)
SFPDML: Securer and Faster Privacy-Preserving Distributed Machine Learning based on MKTFHE
by: Wang, Hongxiao, et al.
Published: (2022)
by: Wang, Hongxiao, et al.
Published: (2022)
SoK: Privacy Preserving Machine Learning using Functional Encryption: Opportunities and Challenges
by: Panzade, Prajwal, et al.
Published: (2022)
by: Panzade, Prajwal, et al.
Published: (2022)
Preserving Privacy and Security in Federated Learning
by: Nguyen, Truc, et al.
Published: (2022)
by: Nguyen, Truc, et al.
Published: (2022)
GuardML: Efficient Privacy-Preserving Machine Learning Services Through Hybrid Homomorphic Encryption
by: Frimpong, Eugene, et al.
Published: (2024)
by: Frimpong, Eugene, et al.
Published: (2024)
Hawk: Accurate and Fast Privacy-Preserving Machine Learning Using Secure Lookup Table Computation
by: Saleem, Hamza, et al.
Published: (2024)
by: Saleem, Hamza, et al.
Published: (2024)
Privacy Preserving Reinforcement Learning for Population Processes
by: Yang-Zhao, Samuel, et al.
Published: (2024)
by: Yang-Zhao, Samuel, et al.
Published: (2024)
SSNet: A Lightweight Multi-Party Computation Scheme for Practical Privacy-Preserving Machine Learning Service in the Cloud
by: Duan, Shijin, et al.
Published: (2024)
by: Duan, Shijin, et al.
Published: (2024)
P3LS: Partial Least Squares under Privacy Preservation
by: Duy, Du Nguyen, et al.
Published: (2024)
by: Duy, Du Nguyen, et al.
Published: (2024)
Improved Privacy-Preserving PCA Using Optimized Homomorphic Matrix Multiplication
by: Ma, Xirong
Published: (2023)
by: Ma, Xirong
Published: (2023)
A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy
by: Li, Xiang, et al.
Published: (2025)
by: Li, Xiang, 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)
by: Effendi, Fabrianne, et al.
Published: (2024)
Privacy Preserving Machine Learning for Electronic Health Records using Federated Learning and Differential Privacy
by: Ganadily, Naif A., et al.
Published: (2024)
by: Ganadily, Naif A., et al.
Published: (2024)
FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning
by: Zeng, Zhihao, et al.
Published: (2025)
by: Zeng, Zhihao, et al.
Published: (2025)
Effectiveness of L2 Regularization in Privacy-Preserving Machine Learning
by: Chandrinos, Nikolaos, et al.
Published: (2024)
by: Chandrinos, Nikolaos, et al.
Published: (2024)
Harnessing Inherent Noises for Privacy Preservation in Quantum Machine Learning
by: Ju, Keyi, et al.
Published: (2023)
by: Ju, Keyi, et al.
Published: (2023)
Preserving Expert-Level Privacy in Offline Reinforcement Learning
by: Sharma, Navodita, et al.
Published: (2024)
by: Sharma, Navodita, et al.
Published: (2024)
Immersion and Invariance-based Coding for Privacy-Preserving Federated Learning
by: Hayati, Haleh, et al.
Published: (2024)
by: Hayati, Haleh, et al.
Published: (2024)
Learning Robust and Privacy-Preserving Representations via Information Theory
by: Zhang, Binghui, et al.
Published: (2024)
by: Zhang, Binghui, et al.
Published: (2024)
Social-Aware Clustered Federated Learning with Customized Privacy Preservation
by: Wang, Yuntao, et al.
Published: (2022)
by: Wang, Yuntao, et al.
Published: (2022)
Machine Learning with Privacy for Protected Attributes
by: Mahloujifar, Saeed, et al.
Published: (2025)
by: Mahloujifar, Saeed, et al.
Published: (2025)
Effective and Efficient Cross-City Traffic Knowledge Transfer: A Privacy-Preserving Perspective
by: Zeng, Zhihao, et al.
Published: (2025)
by: Zeng, Zhihao, et al.
Published: (2025)
DDP-SA: Scalable Privacy-Preserving Federated Learning via Distributed Differential Privacy and Secure Aggregation
by: Wei, Wenjing, et al.
Published: (2026)
by: Wei, Wenjing, et al.
Published: (2026)
A Lightweight and Secure Deep Learning Model for Privacy-Preserving Federated Learning in Intelligent Enterprises
by: Fotohi, Reza, et al.
Published: (2025)
by: Fotohi, Reza, et al.
Published: (2025)
Starlit: Privacy-Preserving Federated Learning to Enhance Financial Fraud Detection
by: Abadi, Aydin, et al.
Published: (2024)
by: Abadi, Aydin, et al.
Published: (2024)
Privacy-Preserving Edge Federated Learning for Intelligent Mobile-Health Systems
by: Aminifar, Amin, et al.
Published: (2024)
by: Aminifar, Amin, et al.
Published: (2024)
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
by: Tang, Xinyu, et al.
Published: (2023)
by: Tang, Xinyu, et al.
Published: (2023)
Data Privacy Preservation on the Internet of Things
by: Sen, Jaydip, et al.
Published: (2023)
by: Sen, Jaydip, et al.
Published: (2023)
Evaluations of Machine Learning Privacy Defenses are Misleading
by: Aerni, Michael, et al.
Published: (2024)
by: Aerni, Michael, et al.
Published: (2024)
Privacy Side Channels in Machine Learning Systems
by: Debenedetti, Edoardo, et al.
Published: (2023)
by: Debenedetti, Edoardo, et al.
Published: (2023)
FT-PrivacyScore: Personalized Privacy Scoring Service for Machine Learning Participation
by: Gu, Yuechun, et al.
Published: (2024)
by: Gu, Yuechun, et al.
Published: (2024)
Privacy-Preserving Generative Models: A Comprehensive Survey
by: Padariya, Debalina, et al.
Published: (2025)
by: Padariya, Debalina, et al.
Published: (2025)
Federated Learning based Latent Factorization of Tensors for Privacy-Preserving QoS Prediction
by: Zhong, Shuai, et al.
Published: (2024)
by: Zhong, Shuai, et al.
Published: (2024)
Similar Items
-
Agentic Privacy-Preserving Machine Learning
by: Zhang, Mengyu, et al.
Published: (2025) -
Automated Privacy-Preserving Techniques via Meta-Learning
by: Carvalho, Tânia, 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) -
Secure Sparse Matrix Multiplications and their Applications to Privacy-Preserving Machine Learning
by: Damie, Marc, et al.
Published: (2025) -
Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM
by: Xie, Chulin, et al.
Published: (2022)