SOTAVerified

Privacy Preserving

Papers

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Showing 1701–1750 of 2975 papers

TitleStatusHype
Fortifying Federated Learning Towards Trustworthiness via Auditable Data Valuation and Verifiable Client Contribution—0
FPGA-Based Hardware Accelerator of Homomorphic Encryption for Efficient Federated Learning—0
FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning—0
Free Lunch for Privacy Preserving Distributed Graph Learning—0
From Models to Network Topologies: A Topology Inference Attack in Decentralized Federated Learning—0
From Private to Public: Benchmarking GANs in the Context of Private Time Series Classification—0
FSAR: Federated Skeleton-based Action Recognition with Adaptive Topology Structure and Knowledge Distillation—0
Secure Embedding Aggregation for Federated Representation Learning—0
Fundamental Limits and Tradeoffs in Invariant Representation Learning—0
Future-Proofing Medical Imaging with Privacy-Preserving Federated Learning and Uncertainty Quantification: A Review—0
G3R: Generating Rich and Fine-grained mmWave Radar Data from 2D Videos for Generalized Gesture Recognition—0
GaitPrivacyON: Privacy-Preserving Mobile Gait Biometrics using Unsupervised Learning—0
GANcrop: A Contrastive Defense Against Backdoor Attacks in Federated Learning—0
Gaussian Mechanisms Against Statistical Inference: Synthesis Tools—0
Gaussian-Smoothed Sliced Probability Divergences—0
Gaussian Splatting Feature Fields for (Privacy-Preserving) Visual Localization—0
GC-Fed: Gradient Centralized Federated Learning with Partial Client Participation—0
GCFL: A Gradient Correction-based Federated Learning Framework for Privacy-preserving CPSS—0
Generalization in Federated Learning: A Conditional Mutual Information Framework—0
Generating Artificial Data for Private Deep Learning—0
Generating Differentially Private Datasets Using GANs—0
Generating Privacy-Preserving Personalized Advice with Zero-Knowledge Proofs and LLMs—0
Generating Privacy-Preserving Process Data with Deep Generative Models—0
Generating Synthetic Data with Formal Privacy Guarantees: State of the Art and the Road Ahead—0
Generating synthetic transactional profiles—0
Generation of Gradient-Preserving Images allowing HOG Feature Extraction—0
Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins?—0
Generative Model-Based Attack on Learnable Image Encryption for Privacy-Preserving Deep Learning—0
GenShare: Sharing Accurate Differentially-Private Statistics for Genomic Datasets with Dependent Tuples—0
GhostVec: A New Threat to Speaker Privacy of End-to-End Speech Recognition System—0
GI-SMN: Gradient Inversion Attack against Federated Learning without Prior Knowledge—0
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces—0
Glyph: Fast and Accurately Training Deep Neural Networks on Encrypted Data—0
Gradient and Channel Aware Dynamic Scheduling for Over-the-Air Computation in Federated Edge Learning Systems—0
A Compressive Sensing Approach for Federated Learning over Massive MIMO Communication Systems—0
Gradient Inversion of Federated Diffusion Models—0
Gradient Obfuscation Gives a False Sense of Security in Federated Learning—0
Gradient Sparsification Can Improve Performance of Differentially-Private Convex Machine Learning—0
GradualDiff-Fed: A Federated Learning Specialized Framework for Large Language Model—0
Graph-Homomorphic Perturbations for Private Decentralized Learning—0
Gromov-Wasserstein Discrepancy with Local Differential Privacy for Distributed Structural Graphs—0
Grounding Foundation Models through Federated Transfer Learning: A General Framework—0
GTV: Generating Tabular Data via Vertical Federated Learning—0
Guaranteed Privacy-Preserving H_-Optimal Interval Observer Design for Bounded-Error LTI Systems—0
GuardNN: Secure Accelerator Architecture for Privacy-Preserving Deep Learning—0
Guided Persona-based AI Surveys: Can we replicate personal mobility preferences at scale using LLMs?—0
Handling Data Heterogeneity with Generative Replay in Collaborative Learning for Medical Imaging—0
Fairness-aware Federated Minimax Optimization with Convergence Guarantee—0
Harnessing Wireless Channels for Scalable and Privacy-Preserving Federated Learning—0
Harvesting Private Medical Images in Federated Learning Systems with Crafted Models—0
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