Adversarial Attacks on Federated-Learned Adaptive Bitrate Algorithms.
Federated Modality-Specific Encoders and Multimodal Anchors for Personalized Brain Tumor Segmentation.
Point Transformer with Federated Learning for Predicting Breast Cancer HER2 Status from Hematoxylin and Eosin-Stained Whole Slide Images.
FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels.
FedCD: Federated Semi-Supervised Learning with Class Awareness Balance via Dual Teachers.
FedST: Federated Style Transfer Learning for Non-IID Image Segmentation.
Diversity-Authenticity Co-constrained Stylization for Federated Domain Generalization in Person Re-identification.
No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation.
Formal Logic Enabled Personalized Federated Learning through Property Inference.
Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning against Attribute Inference Attacks.
FairTrade: Achieving Pareto-Optimal Trade-Offs between Balanced Accuracy and Fairness in Federated Learning.
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators.
FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning.
On Disentanglement of Asymmetrical Knowledge Transfer for Modality-Task Agnostic Federated Learning.
Watch Your Head: Assembling Projection Heads to Save the Reliability of Federated Models.
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity.
FedGCR: Achieving Performance and Fairness for Federated Learning with Distinct Client Types via Group Customization and Reweighting.
Exploiting Label Skews in Federated Learning with Model Concatenation.
FedCSL: A Scalable and Accurate Approach to Federated Causal Structure Learning.
Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space.
FedMut: Generalized Federated Learning via Stochastic Mutation.
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning.
FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing.
Provably Convergent Federated Trilevel Learning.
Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts.
FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning.
EMGAN: Early-Mix-GAN on Extracting Server-Side Model in Split Federated Learning.
Federated X-armed Bandit.
Language-Guided Transformer for Federated Multi-Label Classification.
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update.
UFDA: Universal Federated Domain Adaptation with Practical Assumptions.
Federated Learning with Extremely Noisy Clients via Negative Distillation.
PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning.
A Primal-Dual Algorithm for Hybrid Federated Learning.
Towards Fair Graph Federated Learning via Incentive Mechanisms.
FedLF: Layer-Wise Fair Federated Learning.
Resisting Backdoor Attacks in Federated Learning via Bidirectional Elections and Individual Perspective.
Integer Is Enough: When Vertical Federated Learning Meets Rounding.
CLIP-Guided Federated Learning on Heterogeneity and Long-Tailed Data.
Multi-Dimensional Fair Federated Learning.
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning.
On the Role of Server Momentum in Federated Learning.
FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants.
z-SignFedAvg: A Unified Stochastic Sign-Based Compression for Federated Learning.
Data Disparity and Temporal Unavailability Aware Asynchronous Federated Learning for Predictive Maintenance on Transportation Fleets.
Federated Graph Learning under Domain Shift with Generalizable Prototypes.
TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients.
Multi-Source Collaborative Gradient Discrepancy Minimization for Federated Domain Generalization.
FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise.
Federated Partial Label Learning with Local-Adaptive Augmentation and Regularization.
Federated Causality Learning with Explainable Adaptive Optimization.
Exploring One-Shot Semi-supervised Federated Learning with Pre-trained Diffusion Models.
PerFedRLNAS: One-for-All Personalized Federated Neural Architecture Search.
Efficient Asynchronous Federated Learning with Prospective Momentum Aggregation and Fine-Grained Correction.
FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning.
Knowledge-Aware Parameter Coaching for Personalized Federated Learning.
Federated Label-Noise Learning with Local Diversity Product Regularization.
Complementary Knowledge Distillation for Robust and Privacy-Preserving Model Serving in Vertical Federated Learning.
Towards the Robustness of Differentially Private Federated Learning.
Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users.
Beyond Traditional Threats: A Persistent Backdoor Attack on Federated Learning.
Concealing Sensitive Samples against Gradient Leakage in Federated Learning.
LR-XFL: Logical Reasoning-Based Explainable Federated Learning.
A Huber Loss Minimization Approach to Byzantine Robust Federated Learning.
Federated Learning via Input-Output Collaborative Distillation.
Algorithmic Foundation of Federated Learning with Sequential Data.
General Commerce Intelligence: Glocally Federated NLP-Based Engine for Privacy-Preserving and Sustainable Personalized Services of Multi-Merchants.
HiFi-Gas: Hierarchical Federated Learning Incentive Mechanism Enhanced Gas Usage Estimation.
A Privacy Preserving Federated Learning (PPFL) Based Cognitive Digital Twin (CDT) Framework for Smart Cities.
PICSR: Prototype-Informed Cross-Silo Router for Federated Learning (Student Abstract).
Knowledge Transfer via Compact Model in Federated Learning (Student Abstract).
Adapted Weighted Aggregation in Federated Learning.
Win-Win: A Privacy-Preserving Federated Framework for Dual-Target Cross-Domain Recommendation.
Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense.
Incentive-Boosted Federated Crowdsourcing.
Tackling Data Heterogeneity in Federated Learning with Class Prototypes.
FairFed: Enabling Group Fairness in Federated Learning.
Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning.
Complement Sparsification: Low-Overhead Model Pruning for Federated Learning.
Almost Cost-Free Communication in Federated Best Arm Identification.
Layer-Wise Adaptive Model Aggregation for Scalable Federated Learning.
Poisoning with Cerberus: Stealthy and Colluded Backdoor Attack against Federated Learning.
FedMDFG: Federated Learning with Multi-Gradient Descent and Fair Guidance.
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning.
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing.
Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles between Client Data Subspaces.
FedABC: Targeting Fair Competition in Personalized Federated Learning.
Beyond ADMM: A Unified Client-Variance-Reduced Adaptive Federated Learning Framework.
FedGS: Federated Graph-Based Sampling with Arbitrary Client Availability.
Faster Adaptive Federated Learning.
FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation.
Bayesian Federated Neural Matching That Completes Full Information.
CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems.
Federated Generative Model on Multi-Source Heterogeneous Data in IoT.
DeFL: Defending against Model Poisoning Attacks in Federated Learning via Critical Learning Periods Awareness.
FedALA: Adaptive Local Aggregation for Personalized Federated Learning.
Delving into the Adversarial Robustness of Federated Learning.
On the Vulnerability of Backdoor Defenses for Federated Learning.
Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Model.
DPAUC: Differentially Private AUC Computation in Federated Learning.
Efficient Training of Large-Scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout.
Industry-Scale Orchestrated Federated Learning for Drug Discovery.
A Federated Learning Monitoring Tool for Self-Driving Car Simulation (Student Abstract).
MGIA: Mutual Gradient Inversion Attack in Multi-Modal Federated Learning (Student Abstract).
Clustered Federated Learning for Heterogeneous Data (Student Abstract).
HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images.
FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition.
Federated Learning for Face Recognition with Gradient Correction.
Cross-Modal Federated Human Activity Recognition via Modality-Agnostic and Modality-Specific Representation Learning.
SmartIdx: Reducing Communication Cost in Federated Learning by Exploiting the CNNs Structures.
Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better.
Implicit Gradient Alignment in Distributed and Federated Learning.
SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data.
Is Your Data Relevant?: Dynamic Selection of Relevant Data for Federated Learning.
Federated Nearest Neighbor Classification with a Colony of Fruit-Flies.
FedSoft: Soft Clustered Federated Learning with Proximal Local Updating.
FedProto: Federated Prototype Learning across Heterogeneous Clients.
SplitFed: When Federated Learning Meets Split Learning.
Coordinating Momenta for Cross-Silo Federated Learning.
Seizing Critical Learning Periods in Federated Learning.
A Multi-Agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learning.
FedInv: Byzantine-Robust Federated Learning by Inversing Local Model Updates.
Efficient Device Scheduling with Multi-Job Federated Learning.
Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation.
Contribution-Aware Federated Learning for Smart Healthcare.
Class-Wise Adaptive Self Distillation for Federated Learning on Non-IID Data (Student Abstract).
AsyncFL: Asynchronous Federated Learning Using Majority Voting with Quantized Model Updates (Student Abstract).
FedCC: Federated Learning with Consensus Confirmation for Byzantine Attack Resistance (Student Abstract).
CrowdFL: A Marketplace for Crowdsourced Federated Learning.
Last updated 4 months ago