Application Areas
34,437 papers (4 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Domain Adaptation (9,897)
Efficient Computing (8,226)
Data Augmentation (3,648)
Fairness (3,574)
Knowledge Distillation (3,219)
Privacy (3,022)
Domain Generalization (1,972)
Model Compression (1,736)
Risk Management (1,119)
Model Merging (592)
Recommender Systems (343)
Information Retrieval (249)
Text Classification (144)
Text Processing (2)
Papers per year
1
3
5
5
4
19
24
28
26
35
42
55
142
116
147
330
517
1,020
1,828
2,498
3,411
3,854
5,063
6,422
7,176
1,666
2000
'5
'10
'15
'20
'25
Papers (including subtopics)
Federated Adaptation for Foundation Model-based Recommendations
IJCAI 2024
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning
AAAI 2024
Federated Experiment Design under Distributed Differential Privacy
AISTATS 2024
Federated Graph Learning for Cross-Domain Recommendation
NeurIPS 2024
Federated Graph Learning under Domain Shift with Generalizable Prototypes
AAAI 2024
Federated Learning via Input-Output Collaborative Distillation
AAAI 2024
Federated Learning with Extremely Noisy Clients via Negative Distillation
AAAI 2024
Federated Model Heterogeneous Matryoshka Representation Learning
NeurIPS 2024
Federated Partial Label Learning with Local-Adaptive Augmentation and Regularization
AAAI 2024
Federated Prompt Learning for Weather Foundation Models on Devices
IJCAI 2024
Federated Representation Learning in the Under-Parameterized Regime
ICML 2024
Federated Self-Explaining GNNs with Anti-shortcut Augmentations
ICML 2024
Federated Transformer: Multi-Party Vertical Federated Learning on Practical Fuzzily Linked Data
NeurIPS 2024
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning
AAAI 2024
FedGCR: Achieving Performance and Fairness for Federated Learning with Distinct Client Types via Group Customization and Reweighting
AAAI 2024
FedGMark: Certifiably Robust Watermarking for Federated Graph Learning
NeurIPS 2024
FedGMKD: An Efficient Prototype Federated Learning Framework through Knowledge Distillation and Discrepancy-Aware Aggregation
NeurIPS 2024
FedHCA2: Towards Hetero-Client Federated Multi-Task Learning
CVPR 2024
FedInverse: Evaluating Privacy Leakage in Federated Learning
ICLR 2024
FedLF: Layer-Wise Fair Federated Learning
AAAI 2024
FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees
ICML 2024
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data
ICLR 2024
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation
NeurIPS 2024
FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing
AAAI 2024
FedMBridge: Bridgeable Multimodal Federated Learning
ICML 2024