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From accuracy to approximation: A survey on approximate homomorphic encryption and its applications
W Liu, L You, Y Shao, X Shen, G Hu, J Shi… - Computer Science …, 2025 - Elsevier
Due to the increasing popularity of application scenarios such as cloud computing, and the
growing concern of users about the security and privacy of their data, information security …
growing concern of users about the security and privacy of their data, information security …
Surgical Scene Understanding in the Era of Foundation AI Models: A Comprehensive Review
U Khan, U Nawaz, A Qayyum, S Ashraf, M Bilal… - arxiv preprint arxiv …, 2025 - arxiv.org
Recent advancements in machine learning (ML) and deep learning (DL), particularly
through the introduction of foundational models (FMs), have significantly enhanced surgical …
through the introduction of foundational models (FMs), have significantly enhanced surgical …
DReP: Deep ReLU pruning for fast private inference
P Hu, L Sun, C Hu, L Dai, S Guo, M Yu - Journal of Systems Architecture, 2024 - Elsevier
With increasing concerns about privacy issues in deep learning, privacy-preserving neural
network inference has been receiving growing attention from the community, but the …
network inference has been receiving growing attention from the community, but the …
Advances and Challenges in Privacy-Preserving Machine Learning
S Acheme, GN Edegbe… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
Traditional machine learning relies on collecting data in a centralized location for training
algorithms, this raises privacy concerns, especially when using sensitive information like …
algorithms, this raises privacy concerns, especially when using sensitive information like …
You Only Look Once in Panorama: Object Detection for 360 Videos with MLaaS
360° videos are gaining popularity, but immersive analytics, particularly in object detection,
confront challenges from complex scenes and high data volume. This imposes significant …
confront challenges from complex scenes and high data volume. This imposes significant …
A Systematic Review of Centralized and Decentralized Machine Learning Models: Security Concerns, Defenses and Future Directions
A Samuel, GN Edegbe - NIPES-Journal of Science and …, 2024 - journals.nipes.org
Abstract Models are the heart of machine learning as they represent the end product of the
learning process and help in making predictions. With the widespread adoption of machine …
learning process and help in making predictions. With the widespread adoption of machine …