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Machine Learning
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Federated Learning
551 directly classified papers
Papers per year
2007: 1
2012: 3
2014: 1
2015: 1
2017: 4
2018: 2
2019: 5
2020: 23
2021: 51
2022: 89
2023: 95
2024: 144
2025: 127
2026: 5
Papers
Federated Prompt-Tuning with Heterogeneous and Incomplete Multimodal Client Data
ICCV 2025
Sibai: A Few-Shot Meta-Classifier for Poisoning Detection in Federated Learning
ICCV 2025
Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing
ICCV 2025
You Are Your Own Best Teacher: Achieving Centralized-level Performance in Federated Learning under Heterogeneous and Long-tailed Data
ICCV 2025
Cooperative Pseudo Labeling for Unsupervised Federated Classification
ICCV 2025
MultiSFL: Towards Accurate Split Federated Learning via Multi-Model Aggregation and Knowledge Replay
AAAI 2025
FedMeNF: Privacy-Preserving Federated Meta-Learning for Neural Fields
ICCV 2025
Progressive Distribution Matching for Federated Semi-Supervised Learning
AAAI 2025
LoRA-FAIR: Federated LoRA Fine-Tuning with Aggregation and Initialization Refinement
ICCV 2025
Scalable and Trustworthy Learning in Heterogeneous Networks
AAAI 2025
Stealthy Backdoor Attack in Federated Learning via Adaptive Layer-wise Gradient Alignment
ICCV 2025
Federated Recommendation with Explicitly Encoding Item Bias
AAAI 2025
Sharp Bounds for Sequential Federated Learning on Heterogeneous Data
JMLR 2025
Frequentist Guarantees of Distributed (Non)-Bayesian Inference
JMLR 2025
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
JMLR 2025
Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning
ICCV 2025
PFLlib: A Beginner-Friendly and Comprehensive Personalized Federated Learning Library and Benchmark
JMLR 2025
SADDLe: Sharpness-Aware Decentralized Deep Learning with Heterogeneous Data
WACV 2025
Federated Source-Free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data
WACV 2025
FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning
CVPR 2025
dFLMoE: Decentralized Federated Learning via Mixture of Experts for Medical Data Analysis
CVPR 2025
AFL: A Single-Round Analytic Approach for Federated Learning with Pre-trained Models
CVPR 2025
Population Normalization for Federated Learning
CVPR 2025
A Simple Data Augmentation for Feature Distribution Skewed Federated Learning
CVPR 2025
A Federated Framework for LLM-based Recommendation
NAACL 2025
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