Track Federated Learning Papers
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Explore 1 new papers about IJCAI.
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HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning.
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Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Model.
FedABC: Targeting Fair Competition in Personalized Federated Learning.
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DaFKD: Domain-aware Federated Knowledge Distillation.
Federated Class-Incremental Learning.
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Federated IoT Interaction Vulnerability Analysis.
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STDLens: Model Hijacking-Resilient Federated Learning for Object Detection.
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FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning.
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Active Membership Inference Attack under Local Differential Privacy in Federated Learning.
FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning.
Free-rider Attacks on Model Aggregation in Federated Learning.
Shuffled Model of Differential Privacy in Federated Learning.
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HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning.
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Incentive-Boosted Federated Crowdsourcing.
FedABC: Targeting Fair Competition in Personalized Federated Learning.
DeFL: Defending against Model Poisoning Attacks in Federated Learning via Critical Learning Periods Awareness.
Explore 11 new papers about CVPR.
Securing Federated Sensitive Topic Classification against Poisoning Attacks.
PPA: Preference Profiling Attack Against Federated Learning.
FedCRI: Federated Mobile Cyber-Risk Intelligence.
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning.
Interpretable Federated Transformer Log Learning for Cloud Threat Forensics.
DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection.
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping.
POSEIDON: Privacy-Preserving Federated Neural Network Learning.
Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning.
Strong Authentication without Temper-Resistant Hardware and Application to Federated Identities.
Hardening Persona - Improving Federated Web Login.
Explore 11 new papers about ICCV.
Securing Federated Sensitive Topic Classification against Poisoning Attacks.
PPA: Preference Profiling Attack Against Federated Learning.
FedCRI: Federated Mobile Cyber-Risk Intelligence.
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning.
Interpretable Federated Transformer Log Learning for Cloud Threat Forensics.
DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection.
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping.
POSEIDON: Privacy-Preserving Federated Neural Network Learning.
Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning.
Strong Authentication without Temper-Resistant Hardware and Application to Federated Identities.
Hardening Persona - Improving Federated Web Login.
Explore 11 new papers about ECCV.
Securing Federated Sensitive Topic Classification against Poisoning Attacks.
PPA: Preference Profiling Attack Against Federated Learning.
FedCRI: Federated Mobile Cyber-Risk Intelligence.
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning.
Interpretable Federated Transformer Log Learning for Cloud Threat Forensics.
DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection.
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping.
POSEIDON: Privacy-Preserving Federated Neural Network Learning.
Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning.
Strong Authentication without Temper-Resistant Hardware and Application to Federated Identities.
Hardening Persona - Improving Federated Web Login.
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Securin...
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PrivateFL: Accurate, Differentially Private Federated Learning via Personalized Data Transformation.
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Addressing Heterogeneity in Federated Learning via Distributional Transformation.
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Dim-Krum: Backdoor-Resistant Federated Learning for NLP with Dimension-wise Krum-Based Aggregation.
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A Survey of Federated Evaluation in Federated Learning.
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks.
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data.
SAMBA: A Generic Framework for Secure Federated Multi-Armed Bandits (Extended Abstract).
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.
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 H...
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MSG=## IJCAI
Explore 46 new papers about IJCAI on dblp!
A Survey of Federated Evaluation in Federated Learning.
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks.
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data.
SAMBA: A Generic Framework for Secure Federated Multi-Armed Bandits (Extended Abstract).
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.
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 La...
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An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects.
A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning.
SAGDA: Achieving
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Towards Data-Independent Knowledge Transfer in Model-Heterogeneous Federated Learning.
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Hierarchical Federated Learning With Momentum Acceleration in Multi-Tier Networks.
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Byzantine-Robust Federated Learning with Optimal Statistical Rates.
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Secure Federated Correlation Test and Entropy Estimation.
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FedCE: Personalized Federated Learning Method based on Clustering Ensembles.
FedAA: Using Non-sensitive Modalities to Improve Federated Learning while Preserving Image Privacy.
Federated Deep Multi-View Clustering with Global Self-Supervision.
Prototype-guided Knowledge Transfer for Federated Unsupervised Cross-modal Hashing.
Joint Local Relational Augmentation and Global Nash Equilibrium for Federated Learning with Non-IID Data.
Federated Learning with Label-Masking Distillation.
Cross-Silo Prototypical Calibration for Federated Learning with Non-IID Data.
Client-Adaptive Cross-Model Reconstruction Network for Modality-Incomplete Multimodal Federated Learning.
AffectFAL: Federated Active Affective Computing with Non-IID Data.
Improving Federated Person Re-Identification through Feature-Aware Proximity and Aggregation.
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Privacy as a Resource in Differentially Private Federated Learning.
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Federated Calibration and Evaluation of Binary Classifiers.
FS-Real: A Real-World Cross-Device Federated Learning Platform.
Olive: Oblivious Federated Learning on Trusted Execution Environment Against the Risk of Sparsification.
Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System.
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Explore 15 new papers about conf/sp.
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BARA: Efficient Incentive Mechanism with Online Reward Budget Allocation in Cross-Silo Federated Learning.
Federated Multi-Task Attention for Cross-Individual Human Activity Recognition.
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Iterated Vector Fields and Conservatism, with Applications to Federated Learning.
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Robust federated learning under statistical heterogeneity via hessian-weighted aggregation.
FAC-fed: Federated adaptation for fairness and concept drift aware stream classification.
Ensemble and continual federated learning for classification tasks.
An accurate, scalable and verifiable protocol for federated differentially private averaging.
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A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates.
Attacks against Federated Learning Defense Systems and their Mitigation.
A First Look into the Carbon Footprint of Federated Learning.
Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning.
FedLab: A Flexible Federated Learning Framework.
One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them.
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FedIPR: Ownership Verification for Federated Deep Neural Network Models.
Decentralized Federated Averaging.
Federated Learning Via Inexact ADMM.
Communication-Efficient Randomized Algorithm for Multi-Kernel Online Federated Learning.
Lazily Aggregated Quantized Gradient Innovation for Communication-Efficient Federated Learning.
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FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information.
Scalable and Privacy-Preserving Federated Principal Component Analysis.
SafeFL: MPC-friendly Framework for Private and Robust Federated Learning.
On the Pitfalls of Security Evaluation of Robust Federated Learning.
BayBFed: Bayesian Backdoor Defense for Federated Learning.
3DFed: Adaptive and Extensible Framework for Covert Backdoor Attack in Federated Learning.
RoFL: Robustness of Secure Federated Learning.
Flamingo: Multi-Round Single-Server Secure Aggregation with Applications to Private Federated Learning.
ELSA: Secure Aggregation for Federated Learning with Malicious Actors.
SNARKBlock: Federated Anonymous Blocklisting from Hidden Common Input Aggregate Proofs.
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning.
SAFELearn: Secure Aggregation for private FEderated Learning.
IOTFLA : A Secured and Privacy-Preserving Smart Home Architecture Implementing Federated Learning.
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning.
Privacy by Design in Federated Identity Management.
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Every Vote Counts: Ranking-Based T...
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Explore 5 new papers about DAC.
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Robust Federated Learning with Noisy and Heterogeneous Clients.
FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correction.
Learn from Others and Be Yourself in Heterogeneous Federated Learning.
Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage.
ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning.
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FederatedScope: A Flexible Federated Learning Platform for Heterogeneity.
Federated Calibration and Evaluation of Binary Classifiers.
FS-Real: A Real-World Cross-Device Federated Learning Platform.
Olive: Oblivious Federated Learning on Trusted Execution Environment Against the Risk of Sparsification.
Differentially Private Vertical Federated Clustering.
Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System.
Secure Shapley Value for Cross-Silo Federated Learning.
Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy.
Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Update.
OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization.
FedTSC: A Secure Federated Learning System for Interpretable Time Series Classification.
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Efficient Federated Learning for Modern NLP.
Federated Few-Shot Learning for Mobile NLP.
Federated learning-based air quality prediction for smart cities using BGRU model.
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Arboretum: A Planner for Large-Scale Federated Analytics with Differential Privacy.
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AUCTION: Automated and Quality-Aware Client Selection Framework for Efficient Federated Learning.
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FHDnn: communication efficient and robust federated learning for AIoT networks.
HADFL: Heterogeneity-aware Decentralized Federated Learning Framework.
Helios: Heterogeneity-Aware Federated Learning with Dynamically Balanced Collaboration.
FedLight: Federated Reinforcement Learning for Autonomous Multi-Intersection Traffic Signal Control.
Design and Implementation of a Dynamic Component Model for Federated AUTOSAR Systems.
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Design and Blocking Analysis of Locking Protocols for Real-Time DAG Tasks Under Federated Scheduling.
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Lightweight Blockchain-Empowered Secure and Efficient Federated Edge Learning.
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Dual Personalization on Federated Recommendation.
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Federated Tensor Factorization for Computational Phenotyping.
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Enhancing Decentralized Federated Learning for Non-IID Data on Heterogeneous Devices.
Explore 19 new papers about IJCAI on dblp.
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Explore 19 new papers about IJCAI on dblp.
A Survey of Federated Evaluation in Federated Learning.
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks.
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data.
SAMBA: A Generic Framework for Secure Federated Multi-Armed Bandits (Extended Abstract).
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.
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.
[BARA: Efficient Incentive Mechanism with Online Reward Budget Allo...
Explore 3 new papers about AAAI on dblp.
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Explore 5 new papers about KDD on dblp.
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FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation.
FedALA: Adaptive Local Aggregation for Personalized Federated Learning.
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Optimizing the Collaboration Structure in Cross-Silo Federated Learning.
Anchor Sampling for Federated Learning with Partial Client Participation.
Personalized Federated Learning under Mixture of Distributions.
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Federated online clustering of bandits.
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FedMultimodal: A Benchmark for Multimodal Federated Learning.
FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy.
No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices.
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FLBooster: A Unified and Efficient Platform for Federated Learning Acceleration.
Explore 79 new papers about AAAI.
Explore 79 new papers about AAAI.
FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation.
Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning.
CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems.
Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense.
Tackling Data Heterogeneity in Federated Learning with Class Prototypes.
Delving into the Adversarial Robustness of Federated Learning.
Win-Win: A Privacy-Preserving Federated Framework for Dual-Target Cross-Domain Recommendation.
Efficient Training of Large-Scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout.
FairFed: Enabling Group Fairness in Federated Learning.
On the Vulnerability of Backdoor Defenses for Federated Learning.
Complement Sparsification: Low-Overhead Model Pruning for Federated Learning.
Incentive-Boosted Federated Crowdsourcing.
Almost Cost-Free Communication in Federated Best Arm Identification.
A Federated Learning Monitoring Tool for Self-Driving Car Simulation (Student Abstract).
Layer-Wise Adaptive Model Aggregation for Scalable Federated Learning.
MGIA: Mutual Gradient Inversion Attack in Multi-Modal Federated Learning (Student Abstract).
Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Model.
Poisoning with Cerberus: Stealthy and Colluded Backdoor Attack against Federated Learning.
Industry-Scale Orchestrated Federated Learning for Drug Discovery.
FedMDFG: Federated Learning with Multi-Gradient Descent and Fair Guidance.
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning.
DPAUC: Differentially Private AUC Computation 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.
FedGS: Federated Graph-Based Sampling with Arbitrary Client Availability.
FedABC: Targeting Fair Competition in Personalized Federated Learning.
Beyond ADMM: A Unified Client-Variance-Reduced Adaptive Federated Learning Framework.
Faster Adaptive Federated Learning.
Bayesian Federated Neural Matching That Completes Full Information.
Federated Generative Model on Multi-Source Heterogeneous Data in IoT.
DeFL: Defending against Model Poisoning Attacks in Federated Learning via Critical Learning Periods Awareness.
Clustered Federated Learning for Heterogeneous Data (Student Abstract).
FedALA: Adaptive Local Aggregation for Personalized Federated Learning.
SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data.
Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better.
Implicit Gradient Alignment in Distributed and Federated Learning.
CrowdFL: A Marketplace for Crowdsourced Federated Learning.
Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation.
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).
HarmoFL: Harmonizing Local and Global Drifts...
Explore 2 new papers about journals/pami.
Explore 2 new papers about journals/pami.
Tighter Regret Analysis and Optimization of Online Federated Learning.
Efficient Federated Learning Via Local Adaptive Amended Optimizer With Linear Speedup.
Explore 1 new papers about conf/uss.
Explore 1 new papers about ECCV.
Explore 1 new papers about conf/uss.
PrivateFL: Accurate, Differentially Private Federated Learning via Personalized Data Transformation.
Explore 1 new papers about ECCV.
Addressing Heterogeneity in Federated Learning via Distributional Transformation.
Explore 46 new papers about IJCAI on dblp!
A Survey of Federated Evaluation in Federated Learning.
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks.
Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data.
SAMBA: A Generic Framework for Secure Federated Multi-Armed Bandits (Extended Abstract).
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.
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.
Dual Personalization on Federated Recommendation.
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification.
Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learning.
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting.
Personalized Federated Learning With a Graph.
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning.
Private Semi-Supervised Federated Learning.
Continual Federated Learning Based on Knowledge Distillation.
Poisoning Deep Learning Based Recommender Model in Federated Learning Scenarios.
Federated Multi-Task Attention for Cross-Individual Human Activity Recognition.
Personalized Federated Learning with Contextualized Generalization.
Shielding Federated Learning: Robust Aggregation with Adaptive Client Selection.
Towards Verifiable Federated Learning.
Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization.
Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning.
FedSpeech: Federated Text-to-Speech with Continual Learning.
Practical One-Shot Federated Learning for Cross-Silo Setting.
Federated Model Distillation with Noise-Free Differential Privacy.
LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy.
Federated Learning with Fair Averaging.
Communication-efficient and Scalable Decentralized Federated Edge Learning.
A Multi-player Game for Studying Federated Learning Incentive Schemes.
Federated Meta-Learning for Fraudulent Credit Card Detection.
Multi-Agent Visualization for Explaining Federated Learning.
Explore 79 new papers about AAAI on dblp!
FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation.
CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems.
Tackling Data Heterogeneity in Federated Learning with Class Prototypes.
Delving into the Adversarial Robustness of Federated Learning.
Win-Win: A Privacy-Preserving Federated Framework for Dual-Target Cross-Domain Recommendation.
FairFed: Enabling Group Fairness in Federated Learning.
On the Vulnerability of Backdoor Defenses for Federated Learning.
Complement Sparsification: Low-Overhead Model Pruning for Federated Learning.
Incentive-Boosted Federated Crowdsourcing.
Almost Cost-Free Communication in Federated Best Arm Identification.
A Federated Learning Monitoring Tool for Self-Driving Car Simulation (Student Abstract).
Layer-Wise Adaptive Model Aggregation for Scalable Federated Learning.
MGIA: Mutual Gradient Inversion Attack in Multi-Modal Federated Learning (Student Abstract).
Poisoning with Cerberus: Stealthy and Colluded Backdoor Attack against Federated Learning.
Industry-Scale Orchestrated Federated Learning for Drug Discovery.
FedMDFG: Federated Learning with Multi-Gradient Descent and Fair Guidance.
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning.
DPAUC: Differentially Private AUC Computation in Federated Learning.
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing.
FedGS: Federated Graph-Based Sampling with Arbitrary Client Availability.
FedABC: Targeting Fair Competition in Personalized Federated Learning.
Beyond ADMM: A Unified Client-Variance-Reduced Adaptive Federated Learning Framework.
Faster Adaptive Federated Learning.
Bayesian Federated Neural Matching That Completes Full Information.
Federated Generative Model on Multi-Source Heterogeneous Data in IoT.
Clustered Federated Learning for Heterogeneous Data (Student Abstract).
FedALA: Adaptive Local Aggregation for Personalized Federated Learning.
SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data.
Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better.
Implicit Gradient Alignment in Distributed and Federated Learning.
CrowdFL: A Marketplace for Crowdsourced Federated Learning.
Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation.
Class-Wise Adaptive Self Distillation for Federated Learning on Non-IID Data (Student Abstract).
HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images.
Contribution-Aware Federated Learning for Smart Healthcare.
FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition.
Is Your Data Relevant?: Dynamic Selection of Relevant Data for Federated Learning.
Federated Learning for Face Recognition with Gradient Correction.
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.
SmartIdx: Reducing Communication Cost in Federated Learning by Exploiting the CNNs Structures.
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.
Provably Secure Federated Learning against Malicious Clients.
Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation.
On the Convergence of Communication-Efficient Local SGD for Federated Learning.
Personalized Cross-Silo Federated Learning on Non-IID Data.
FedRec++: Lossless Federated Recommendation with Explicit Feedback.
FLAME: Differentially Private Federated Learning in the Shuffle Model.
Game of Gradients: Mitigating Irrelevant Clients in Federated Learning.
Defending against Backdoors in Federated Learning with Robust Learning Rate.
Federated Multi-Armed Bandits.
Addressing Class Imbalance in Federated Learning.
Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models.
Toward Understanding the Influence of Individual Clients in Federated Learning.
Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning.
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating.
Robust Federated Learning via Collaborative Machine Teaching.
Practical Federated Gradient Boosting Decision Trees.
FedVision: An Online Visual Object Detection Platform Powered by Federated Learning.
Federated Learning for Vision-and-Language Grounding Problems.
Federated Latent Dirichlet Allocation: A Local Differential Privacy Based Framework.
Mechanism Design for Federated Sponsored Search Auctions.
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Federated Asymptotics: a model to compare federated learning algorithms.
The communication cost of security and privacy in federated frequency estimation.
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout.
Federated Learning under Distributed Concept Drift.
Characterizing Internal Evasion Attacks in Federated Learning.
Private Non-Convex Federated Learning Without a Trusted Server.
Federated Learning for Data Streams.
Nothing but Regrets - Privacy-Preserving Federated Causal Discovery.
[Active Membership Inference Attack under Local Differential Privacy in Feder...
Explore 2 new papers about AAAI.
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MGIA: Mutual Gradient Inversion Attack in Multi-Modal Federated Learning (Student Abstract).
FedABC: Targeting Fair Competition in Personalized Federated Learning.
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Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape.
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Make Landscape Flatter in Differentially Private Federated Learning.
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CriticalFL: A Critical Learning Periods Augmented Client Selection Framework for Efficient Federated Learning.
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Federated Node Classification over Graphs with Latent Link-type Heterogeneity.
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Eiffel: Efficient and Fair Scheduling in Adaptive Federated Learning.
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Explore 2 new papers about KDD on dblp.
Theoretical Convergence Guaranteed Resource-Adaptive Federated Learning with Mixed Heterogeneity.
Collaboration Equilibrium in Federated Learning.
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FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning.
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Practical Lossless Federated Singular Vector Decomposition over Billion-Scale Data.
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Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization.
Elastic Aggregation for Federated Optimization.
STDLens: Model Hijacking-Resilient Federated Learning for Object Detection.
Rethinking Federated Learning with Domain Shift: A Prototype View.
ScaleFL: Resource-Adaptive Federated Learning with Heterogeneous Clients.
Fair Federated Medical Image Segmentation via Client Contribution Estimation.
Class Balanced Adaptive Pseudo Labeling for Federated Semi-Supervised Learning.
On the Effectiveness of Partial Variance Reduction in Federated Learning with Heterogeneous Data.
Adaptive Channel Sparsity for Federated Learning under System Heterogeneity.
Reliable and Interpretable Personalized Federated Learning.
How to Prevent the Poor Performance Clients for Personalized Federated Learning?
Make Landscape Flatter in Differentially Private Federated Learning.
DaFKD: Domain-aware Federated Knowledge Distillation.
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning.
Bias-Eliminating Augmentation Learning for Debiased Federated Learning.
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FLASH: Towards a High-performance Hardware Acceleration Architecture for Cross-silo Federated Learning.
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Federated Submodel Optimization for Hot and Cold Data Features.
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Revisiting Weighted Aggregation in Federated Learning with Neural Networks.
Federated Conformal Predictors for Distributed Uncertainty Quantification.
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AffectFAL: Federated Active Affective Computing with Non-IID Data.
Feeling Without Sharing: A Federated Video Emotion Recognition Framework Via Privacy-Agnostic Hybrid Aggregation.
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Edge-cloud Collaborative Learning with Federated and Centralized Features.
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SafeFL: MPC-friendly Framework for Private and Robust Federated Learning.
On the Pitfalls of Security Evaluation of Robust Federated Learning.
SNARKBlock: Federated Anonymous Blocklisting from Hidden Common Input Aggregate Proofs.
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning.
SAFELearn: Secure Aggregation for private FEderated Learning.
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Explore 2 new papers about CVPR.
STDLens: Model Hijacking-Resilient Federated Learning for Object Detection.
Class Balanced Adaptive Pseudo Labeling for Federated Semi-Supervised Learning.
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Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs.
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Privacy-preserving graph convolution network for federated item recommendation.
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The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond.
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Hardening Persona - Improving Federated Web Login.
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Securing Federated Sensitive Topic Classification against Poisoning Attacks.
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Explore 3 new papers about KDD on dblp.
Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation.
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Explore 3 new papers about AISTATS.
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms.
Byzantine-Robust Federated Learning with Optimal Statistical Rates.
Towards Understanding Biased Client Selection in Federated Learning.
Explore 26 new papers about INFOCOM.
Explore 26 new papers about INFOCOM.
A Hierarchical Knowledge Transfer Framework for Heterogeneous Federated Learning.
Joint Participation Incentive and Network Pricing Design for Federated Learning.
Enabling Communication-Efficient Federated Learning via Distributed Compressed Sensing.
SplitGP: Achieving Both Generalization and Personalization in Federated Learning.
Network Adaptive Federated Learning: Congestion and Lossy Compression.
Heterogeneity-Aware Federated Learning with Adaptive Client Selection and Gradient Compression.
AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices.
FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning.
Adaptive Configuration for Heterogeneous Participants in Decentralized Federated Learning.
Communication-Efficient Federated Learning for Heterogeneous Edge Devices Based on Adaptive Gradient Quantization.
Federated PCA on Grassmann Manifold for Anomaly Detection in IoT Networks.
Federated Learning under Heterogeneous and Correlated Client Availability.
Asynchronous Federated Unlearning.
Tackling System Induced Bias in Federated Learning: Stratification and Convergence Analysis.
FedMoS: Taming Client Drift in Federated Learning with Double Momentum and Adaptive Selection.
More than Enough is Too Much: Adaptive Defenses against Gradient Leakage in Production Federated Learning.
Toward Sustainable AI: Federated Learning Demand Response in Cloud-Edge Systems via Auctions.
SVDFed: Enabling Communication-Efficient Federated Learning via Singular-Value-Decomposition.
Federated Learning with Flexible Control.
AOCC-FL: Federated Learning with Aligned Overlapping via Calibrated Compensation.
TVFL: Tunable Vertical Federated Learning towards Communication-Efficient Model Serving.
Joint Edge Aggregation and Association for Cost-Efficient Multi-Cell Federated Learning.
Privacy as a Resource in Differentially Private Federated Learning.
Oblivion: Poisoning Federated Learning by Inducing Catastrophic Forgetting.
Truthful Incentive Mechanism for Federated Learning with Crowdsourced Data Labeling.
A Reinforcement Learning Approach for Minimizing Job Completion Time in Clustered Federated Learning.
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Explore 4 new papers about journals/pvldb.
Federated Calibration and Evaluation of Binary Classifiers.
FS-Real: A Real-World Cross-Device Federated Learning Platform.
Olive: Oblivious Federated Learning on Trusted Execution Environment Against the Risk of Sparsification.
Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System.
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Explore 4 new papers about NAACL-HLT on dblp.
FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks.
Training Mixed-Domain Translation Models via Federated Learning.
Federated Learning with Noisy User Feedback.
Pretrained Models for Multilingual Federated Learning.
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Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning.
Fast Federated Machine Unlearning with Nonlinear Functional Theory.
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift.
Improving the Model Consistency of Decentralized Federated Learning.
Private Federated Learning with Autotuned Compression.
TabLeak: Tabular Data Leakage in Federated Learning.
FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization.
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond.
Anchor Sampling for Federated Learning with Partial Client Participation.
Personalized Federated Learning under Mixture of Distributions.
Personalized Federated Learning with Inferred Collaboration Graphs.
FedDisco: Federated Learning with Discrepancy-Aware Collaboration.
Doubly Adversarial Federated Bandits.
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Explore 7 new papers about conf/mm.
Towards Fast and Stable Federated Learning: Confronting Heterogeneity via Knowledge Anchor.
FedVQA: Personalized Federated Visual Question Answering over Heterogeneous Scenes.
Prototype-guided Knowledge Transfer for Federated Unsupervised Cross-modal Hashing.
FedCD: A Classifier Debiased Federated Learning Framework for Non-IID Data.
A Four-Pronged Defense Against Byzantine Attacks in Federated Learning.
FedGH: Heterogeneous Federated Learning with Generalized Global Header.
Cuing Without Sharing: A Federated Cued Speech Recognition Framework via Mutual Knowledge Distillation.
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Explore 2 new papers about journals/ml.
FAC-fed: Federated adaptation for fairness and concept drift aware stream classification.
Ensemble and continual federated learning for classification tasks.
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
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TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
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The Web framework for perfectionists with deadlines.
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Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
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China tencent open source team.
