Federated Learning

Federated Learning is a machine learning approach that allows multiple devices or entities to collaboratively train a shared model without exchanging their data with each other. Instead of sending data to a central server for training, the model is trained locally on each device, and only the model updates are sent to the central server, where they are aggregated to improve the shared model.

This approach allows for privacy-preserving machine learning, as each device keeps its data locally and only shares the information needed to improve the model.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 5401–5450 of 6771 papers

Title	Date	Tasks	Status	Hype
Practical and Private Heterogeneous Federated Learning	Sep 29, 2021	Federated LearningPrivacy Preserving	—Unverified	0
Federated Contrastive Representation Learning with Feature Fusion and Neighborhood Matching	Sep 29, 2021	Contrastive LearningFederated Learning	—Unverified	0
Robust and Personalized Federated Learning with Spurious Features: an Adversarial Approach	Sep 29, 2021	Federated LearningPersonalized Federated Learning	—Unverified	0
FedDiscrete: A Secure Federated Learning Algorithm Against Weight Poisoning	Sep 29, 2021	Federated Learning	—Unverified	0
Adapt to Adaptation: Learning to Personalize for Cross-Silo Federated Learning	Sep 29, 2021	Federated Learning	—Unverified	0
Secure Byzantine-Robust Federated Learning with Dimension-free Error	Sep 29, 2021	Federated Learning	—Unverified	0
Hybrid Local SGD for Federated Learning with Heterogeneous Communications	Sep 29, 2021	Federated Learning	—Unverified	0
FedBABU: Toward Enhanced Representation for Federated Image Classification	Sep 29, 2021	ClassificationFederated Learning	—Unverified	0
An Agnostic Approach to Federated Learning with Class Imbalance	Sep 29, 2021	Federated Learning	—Unverified	0
Distributed Skellam Mechanism: a Novel Approach to Federated Learning with Differential Privacy	Sep 29, 2021	Federated LearningMath	—Unverified	0
Fairness-aware Federated Learning	Sep 29, 2021	FairnessFederated Learning	—Unverified	0
FSL: Federated Supermask Learning	Sep 29, 2021	Federated Learning	—Unverified	0
RVFR: Robust Vertical Federated Learning via Feature Subspace Recovery	Sep 29, 2021	Federated LearningVertical Federated Learning	—Unverified	0
Scalable Robust Federated Learning with Provable Security Guarantees	Sep 29, 2021	Federated Learning	—Unverified	0
Picking Daisies in Private: Federated Learning from Small Datasets	Sep 29, 2021	Federated Learning	—Unverified	0
Unsupervised Federated Learning is Possible	Sep 29, 2021	Federated Learning	—Unverified	0
Certified Robustness for Free in Differentially Private Federated Learning	Sep 29, 2021	Federated Learning	—Unverified	0
Towards Generalizable Personalized Federated Learning with Adaptive Local Adaptation	Sep 29, 2021	Federated LearningMeta-Learning	—Unverified	0
Coordinated Attacks Against Federated Learning: A Multi-Agent Reinforcement Learning Approach	Sep 29, 2021	Federated LearningMulti-agent Reinforcement Learning	—Unverified	0
FEDERATED LEARNING FRAMEWORK BASED ON TRIMMED MEAN AGGREGATION RULES	Sep 29, 2021	Federated Learning	—Unverified	0
FedDrop: Trajectory-weighted Dropout for Efficient Federated Learning	Sep 29, 2021	Federated Learning	—Unverified	0
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions	Sep 29, 2021	Federated Learningimage-classification	—Unverified	0
LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning	Sep 29, 2021	Federated Learning	—Unverified	0
Secure Multi-Party Computation based Privacy Preserving Data Analysis in Healthcare IoT Systems	Sep 29, 2021	Federated LearningPrivacy Preserving	—Unverified	0
Towards Communication-Efficient and Privacy-Preserving Federated Representation Learning	Sep 29, 2021	Contrastive LearningFederated Learning	—Unverified	0
Private Language Model Adaptation for Speech Recognition	Sep 28, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Federated Learning Algorithms for Generalized Mixed-effects Model (GLMM) on Horizontally Partitioned Data from Distributed Sources	Sep 28, 2021	Federated Learning	—Unverified	0
FedIPR: Ownership Verification for Federated Deep Neural Network Models	Sep 27, 2021	Federated Learning	CodeCode Available	1
Federated Deep Learning with Bayesian Privacy	Sep 27, 2021	Deep LearningFederated Learning	—Unverified	0
MixNN: Protection of Federated Learning Against Inference Attacks by Mixing Neural Network Layers	Sep 26, 2021	AttributeFederated Learning	—Unverified	0
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization	Sep 26, 2021	Federated LearningPrivacy Preserving	—Unverified	0
Communication-Efficient Federated Linear and Deep Generalized Canonical Correlation Analysis	Sep 25, 2021	Distributed ComputingDistributed Optimization	CodeCode Available	0
FedProc: Prototypical Contrastive Federated Learning on Non-IID data	Sep 25, 2021	Federated Learningimage-classification	CodeCode Available	1
SGDE: Secure Generative Data Exchange for Cross-Silo Federated Learning	Sep 24, 2021	BIG-bench Machine LearningFairness	—Unverified	0
Backdoor Attacks on Federated Learning with Lottery Ticket Hypothesis	Sep 22, 2021	Backdoor AttackFederated Learning	CodeCode Available	1
Improving Fairness for Data Valuation in Horizontal Federated Learning	Sep 19, 2021	Data ValuationFairness	—Unverified	0
Splitfed learning without client-side synchronization: Analyzing client-side split network portion size to overall performance	Sep 19, 2021	Federated Learningimage-classification	—Unverified	0
Toward Efficient Federated Learning in Multi-Channeled Mobile Edge Network with Layerd Gradient Compression	Sep 18, 2021	Federated Learning	—Unverified	0
Comfetch: Federated Learning of Large Networks on Constrained Clients via Sketching	Sep 17, 2021	Federated Learning	—Unverified	0
Enforcing fairness in private federated learning via the modified method of differential multipliers	Sep 17, 2021	BIG-bench Machine LearningFairness	—Unverified	0
Achieving Model Fairness in Vertical Federated Learning	Sep 17, 2021	BIG-bench Machine LearningFairness	CodeCode Available	0
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework	Sep 16, 2021	Federated Learning	CodeCode Available	1
Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer	Sep 16, 2021	Federated LearningPersonalized Federated Learning	—Unverified	0
Connecting Low-Loss Subspace for Personalized Federated Learning	Sep 16, 2021	Ensemble LearningFederated Learning	CodeCode Available	1
Federated Submodel Optimization for Hot and Cold Data Features	Sep 16, 2021	Federated Learning	CodeCode Available	0
Federated Contrastive Learning for Decentralized Unlabeled Medical Images	Sep 15, 2021	Contrastive LearningData Augmentation	—Unverified	0
Federated Learning of Molecular Properties with Graph Neural Networks in a Heterogeneous Setting	Sep 15, 2021	Federated Learning	—Unverified	0
Bayesian AirComp with Sign-Alignment Precoding for Wireless Federated Learning	Sep 14, 2021	Federated Learning	—Unverified	0
AMI-FML: A Privacy-Preserving Federated Machine Learning Framework for AMI	Sep 13, 2021	BIG-bench Machine Learningenergy management	—Unverified	0
Concept Drift Detection in Federated Networked Systems	Sep 13, 2021	Dimensionality ReductionDrift Detection	—Unverified	0

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All datasets Cityscapes heterogeneous Landmarks-User-160k CIFAR-100 (alpha=0, 10 clients per round)CIFAR-100 (alpha=0, 20 clients per round)CIFAR-100 (alpha=0.5, 10 clients per round)CIFAR-100 (alpha=0.5, 20 clients per round)CIFAR-100 (alpha=0.5, 5 clients per round)CIFAR-100 (alpha=0, 5 clients per round)CIFAR-100 (alpha=1000, 10 clients per round)CIFAR-100 (alpha=1000, 20 clients per round)CIFAR-100 (alpha=1000, 5 clients per round)CIFAR100 (alpha=0.3, 10 clients per round)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	SiloBN + ASAM	mIoU	49.75	—	Unverified
2	SiloBN + SAM	mIoU	49.1	—	Unverified
3	SiloBN	mIoU	45.96	—	Unverified
4	FedSAM + SWA	mIoU	43.42	—	Unverified
5	FedASAM + SWA	mIoU	43.02	—	Unverified
6	FedAvg + SWA	mIoU	42.48	—	Unverified
7	FedASAM	mIoU	42.27	—	Unverified
8	FedSAM	mIoU	41.22	—	Unverified
9	FedAvg	mIoU	38.65	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	Acc@1-1262Clients	68.32	—	Unverified
2	FedSAM + SWA	Acc@1-1262Clients	68.12	—	Unverified
3	FedAvg + SWA	Acc@1-1262Clients	67.52	—	Unverified
4	FedASAM	Acc@1-1262Clients	64.23	—	Unverified
5	FedSAM	Acc@1-1262Clients	63.72	—	Unverified
6	FedAvg	Acc@1-1262Clients	61.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	ACC@1-100Clients	42.64	—	Unverified
2	FedASAM	ACC@1-100Clients	39.76	—	Unverified
3	FedSAM + SWA	ACC@1-100Clients	39.51	—	Unverified
4	FedSAM	ACC@1-100Clients	36.93	—	Unverified
5	FedAvg	ACC@1-100Clients	36.74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	ACC@1-100Clients	41.62	—	Unverified
2	FedASAM	ACC@1-100Clients	40.81	—	Unverified
3	FedSAM + SWA	ACC@1-100Clients	39.24	—	Unverified
4	FedAvg	ACC@1-100Clients	38.59	—	Unverified
5	FedSAM	ACC@1-100Clients	38.56	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	ACC@1-100Clients	48.72	—	Unverified
2	FedSAM + SWA	ACC@1-100Clients	46.76	—	Unverified
3	FedASAM	ACC@1-100Clients	46.58	—	Unverified
4	FedSAM	ACC@1-100Clients	44.84	—	Unverified
5	FedAvg	ACC@1-100Clients	41.27	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	ACC@1-100Clients	48.27	—	Unverified
2	FedASAM	ACC@1-100Clients	47.78	—	Unverified
3	FedSAM + SWA	ACC@1-100Clients	46.47	—	Unverified
4	FedSAM	ACC@1-100Clients	46.05	—	Unverified
5	FedAvg	ACC@1-100Clients	42.17	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	ACC@1-100Clients	49.17	—	Unverified
2	FedSAM + SWA	ACC@1-100Clients	47.96	—	Unverified
3	FedASAM	ACC@1-100Clients	45.61	—	Unverified
4	FedSAM	ACC@1-100Clients	44.73	—	Unverified
5	FedAvg	ACC@1-100Clients	40.43	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM + SWA	ACC@1-100Clients	42.01	—	Unverified
2	FedSAM + SWA	ACC@1-100Clients	39.3	—	Unverified
3	FedASAM	ACC@1-100Clients	36.04	—	Unverified
4	FedSAM	ACC@1-100Clients	31.04	—	Unverified
5	FedAvg	ACC@1-100Clients	30.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM	ACC@1-100Clients	54.97	—	Unverified
2	FedASAM + SWA	ACC@1-100Clients	54.79	—	Unverified
3	FedSAM + SWA	ACC@1-100Clients	53.67	—	Unverified
4	FedSAM	ACC@1-100Clients	53.39	—	Unverified
5	FedAvg	ACC@1-100Clients	50.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM	ACC@1-100Clients	54.5	—	Unverified
2	FedSAM + SWA	ACC@1-100Clients	54.36	—	Unverified
3	FedASAM + SWA	ACC@1-100Clients	54.1	—	Unverified
4	FedSAM	ACC@1-100Clients	53.97	—	Unverified
5	FedAvg	ACC@1-100Clients	50.66	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FedASAM	ACC@1-100Clients	54.81	—	Unverified
2	FedSAM	ACC@1-100Clients	54.01	—	Unverified
3	FedSAM + SWA	ACC@1-100Clients	53.9	—	Unverified
4	FedASAM + SWA	ACC@1-100Clients	53.86	—	Unverified
5	FedAvg	ACC@1-100Clients	49.92	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	AdaBest	Average Top-1 Accuracy	56.2	—	Unverified