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Privacy Preserving

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Showing 1201–1225 of 2975 papers

TitleStatusHype
FATE-LLM: A Industrial Grade Federated Learning Framework for Large Language ModelsCode2
Optimized Layerwise Approximation for Efficient Private Inference on Fully Homomorphic Encryption—0
Federated Battery Diagnosis and Prognosis—0
Addressing the cold start problem in privacy preserving content-based recommender systems using hypercube graphs—0
Wasm-iCARE: a portable and privacy-preserving web module to build, validate, and apply absolute risk modelsCode0
Split-and-Denoise: Protect large language model inference with local differential privacyCode1
Privacy-Preserving Encrypted Low-Dose CT Denoising—0
Histopathological Image Classification and Vulnerability Analysis using Federated Learning—0
RaftFed: A Lightweight Federated Learning Framework for Vehicular Crowd Intelligence—0
Federated Quantum Machine Learning with Differential Privacy—0
Exploring adversarial attacks in federated learning for medical imaging—0
Federated Learning with Reduced Information Leakage and ComputationCode0
Towards Scalable Wireless Federated Learning: Challenges and Solutions—0
A privacy-preserving method using secret key for convolutional neural network-based speech classification—0
Quantized Transformer Language Model Implementations on Edge Devices—0
V2X Cooperative Perception for Autonomous Driving: Recent Advances and Challenges—0
Shielding the Unseen: Privacy Protection through Poisoning NeRF with Spatial Deformation—0
Privacy-preserving Multi-biometric Indexing based on Frequent Binary Patterns—0
Exploring the Impact of Disrupted Peer-to-Peer Communications on Fully Decentralized Learning in Disaster Scenarios—0
The Inhibitor: ReLU and Addition-Based Attention for Efficient Transformers—0
Artemis: HE-Aware Training for Efficient Privacy-Preserving Machine Learning—0
FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models—0
Privacy-Preserving Distributed Market Mechanism for Active Distribution Networks—0
Bridging the Gap Between Foundation Models and Heterogeneous Federated Learning—0
Beyond Random Noise: Insights on Anonymization Strategies from a Latent Bandit Study—0
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