PLDP-FL: Federated Learning with Personalized Local Differential Privacy. [PDF]
Entropy (Basel), 2023 Shen X, Jiang H, Chen Y, Wang B, Gao L.
europepmc +1 more source
Mining Frequent Graph Patterns with Differential Privacy
, 2013 Entong Shen, Ting Yu
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Photonic Nanomaterials for Wearable Health Solutions
Advanced Materials, EarlyView.This review discusses the fundamentals and applications of photonic nanomaterials in wearable health technologies. It covers light‐matter interactions, synthesis, and functionalization strategies, device assembly, and sensing capabilities. Applications include skin patches and contact lenses for diagnostics and therapy. Future perspectives emphasize AI‐
Taewoong Park +3 more
wiley +1 more source
Federated transfer learning with differential privacy for multi-omics survival analysis. [PDF]
Brief BioinformWen G, Li L.
europepmc +1 more source
E-DPNCT: an enhanced attack resilient differential privacy model for smart grids using split noise cancellation. [PDF]
Sci Rep, 2023 Hafeez K, O'Shea D, Newe T, Rehmani MH.
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Understanding the sparse vector technique for differential privacy [PDF]
, 2017 Min Lyu, Dong Su, Ninghui Li
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Smart Dust for Chemical Mapping
Advanced Materials, EarlyView.This review article explores the advancement of smart dust networks for high‐resolution spatial and temporal chemical mapping. Comprising miniature, wireless sensors, and communication devices, smart dust autonomously collects, processes, and transmits data via swarm‐based communication.
Indrajit Mondal, Hossam Haick
wiley +1 more source
Advanced Materials, Volume 37, Issue 13, April 2, 2025.A single object with dual properties – degradable and non‐degradable – is fabricated in a single print simply by switching the printing colors. The advanced multi‐material printing is enabled by the combination of a fully wavelength‐orthogonal photoresin and a monochromatic tunable laser printer, paving the way for precise multi‐material ...
Xingyu Wu +5 more
wiley +1 more source
When Differential Privacy Meets Randomized Perturbation: A Hybrid Approach for Privacy-Preserving Recommender System [PDF]
, 2017 Xiao Liu +6 more
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A Communication-Efficient, Privacy-Preserving Federated Learning Algorithm Based on Two-Stage Gradient Pruning and Differentiated Differential Privacy. [PDF]
Sensors (Basel), 2023 Li Y, Du W, Han L, Zhang Z, Liu T.
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