SOTAVerified

Privacy Preserving

Papers

Showing 14261450 of 2975 papers

TitleStatusHype
Divide-and-Conquer the NAS puzzle in Resource Constrained Federated Learning Systems0
PerFedRec++: Enhancing Personalized Federated Recommendation with Self-Supervised Pre-Training0
A Platform for the Biomedical Application of Large Language ModelsCode1
Privacy-Preserving Prompt Tuning for Large Language Model Services0
Synthetic Query Generation for Privacy-Preserving Deep Retrieval Systems using Differentially Private Language Models0
Collaborative Chinese Text Recognition with Personalized Federated Learning0
Turning Privacy-preserving Mechanisms against Federated Learning0
FedPDD: A Privacy-preserving Double Distillation Framework for Cross-silo Federated Recommendation0
FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise HeterogeneityCode1
A Feasibility Study on Indoor Localization and Multi-person Tracking Using Sparsely Distributed Camera Network with Edge ComputingCode0
Privacy-Preserving Representations are not Enough -- Recovering Scene Content from Camera PosesCode0
Privacy-preserving Adversarial Facial Features0
Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning via Data Generation and Parameter Distortion0
Exploring One-shot Semi-supervised Federated Learning with A Pre-trained Diffusion Model0
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information0
An Overview of AI and Blockchain Integration for Privacy-Preserving0
Gradient Leakage Defense with Key-Lock Module for Federated LearningCode0
Adversarially-Guided Portrait MattingCode1
Efficient Federated Learning with Enhanced Privacy via Lottery Ticket Pruning in Edge Computing0
Privacy-Preserving In-Context Learning for Large Language Models0
A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models0
Training Large Scale Polynomial CNNs for E2E Inference over Homomorphic Encryption0
Bayesian Federated Learning: A Survey0
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models0
(Local) Differential Privacy has NO Disparate Impact on FairnessCode0
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