EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated Learning.
BADFSS: Backdoor Attacks on Federated Self-Supervised Learning.
Enhancing Dual-Target Cross-Domain Recommendation with Federated Privacy-Preserving Learning.
Estimating before Debiasing: A Bayesian Approach to Detaching Prior Bias in Federated Semi-Supervised Learning.
LG-FGAD: An Effective Federated Graph Anomaly Detection Framework.
Breaking Barriers of System Heterogeneity: Straggler-Tolerant Multimodal Federated Learning via Knowledge Distillation.
Federated Multi-View Clustering via Tensor Factorization.
Efficient Federated Multi-View Clustering with Integrated Matrix Factorization and K-Means.
Unlearning during Learning: An Efficient Federated Machine Unlearning Method.
Sample Quality Heterogeneity-aware Federated Causal Discovery through Adaptive Variable Space Selection.
Feature Norm Regularized Federated Learning: Utilizing Data Disparities for Model Performance Gains.
Practical Hybrid Gradient Compression for Federated Learning Systems.
DarkFed: A Data-Free Backdoor Attack in Federated Learning.
FedConPE: Efficient Federated Conversational Bandits with Heterogeneous Clients.
Scalable Federated Unlearning via Isolated and Coded Sharding.
LEAP: Optimization Hierarchical Federated Learning on Non-IID Data with Coalition Formation Game.
FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization.
FedPFT: Federated Proxy Fine-Tuning of Foundation Models.
Dual Calibration-based Personalised Federated Learning.
A Bias-Free Revenue-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning.
Redefining Contributions: Shapley-Driven Federated Learning.
From Optimization to Generalization: Fair Federated Learning against Quality Shift via Inter-Client Sharpness Matching.
FedFa: A Fully Asynchronous Training Paradigm for Federated Learning.
FBLG: A Local Graph Based Approach for Handling Dual Skewed Non-IID Data in Federated Learning.
FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning.
FedES: Federated Early-Stopping for Hindering Memorizing Heterogeneous Label Noise.
Federated Adaptation for Foundation Model-based Recommendations.
Personalized Federated Learning for Cross-City Traffic Prediction.
FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning.
Federated Prompt Learning for Weather Foundation Models on Devices.
Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks.
Label Leakage in Vertical Federated Learning: A Survey.
Knowledge Distillation in Federated Learning: A Practical Guide.
A Systematic Survey on Federated Semi-supervised Learning.
Intelligent Agents for Auction-based Federated Learning: A Survey.
A Survey on Efficient Federated Learning Methods for Foundation Model Training.
Stakeholder-oriented Decision Support for Auction-based Federated Learning.
The Rise of Federated Intelligence: From Federated Foundation Models Toward Collective Intelligence.
Federated Probabilistic Preference Distribution Modelling with Compactness Co-Clustering for Privacy-Preserving Multi-Domain Recommendation.
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data.
FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning.
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks.
FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation.
Globally Consistent Federated Graph Autoencoder for Non-IID Graphs.
Federated Graph Semantic and Structural Learning.
HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning.
FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer.
FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment.
FedSampling: A Better Sampling Strategy for Federated Learning.
Competitive-Cooperative Multi-Agent Reinforcement Learning for Auction-based Federated Learning.
FedBFPT: An Efficient Federated Learning Framework for Bert Further Pre-training.
FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity.
BARA: Efficient Incentive Mechanism with Online Reward Budget Allocation in Cross-Silo Federated Learning.
Dual Personalization on Federated Recommendation.
Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning.
A Survey of Federated Evaluation in Federated Learning.
SAMBA: A Generic Framework for Secure Federated Multi-Armed Bandits (Extended Abstract).
Shielding Federated Learning: Robust Aggregation with Adaptive Client Selection.
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification.
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting.
Private Semi-Supervised Federated Learning.
Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learning.
Continual Federated Learning Based on Knowledge Distillation.
Poisoning Deep Learning Based Recommender Model in Federated Learning Scenarios.
Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features.
Personalized Federated Learning with Contextualized Generalization.
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning.
Personalized Federated Learning With a Graph.
FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server.
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning.
Federated Multi-Task Attention for Cross-Individual Human Activity Recognition.
Towards Verifiable Federated Learning.
Last updated 4 months ago