zewei-long / fedcon-pytorch
A PyTorch implementation for the paper FedCon: A Contrastive Framework for Federated Semi-Supervised Learning.
☆19Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for fedcon-pytorch
- ICML2022: Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning☆40Updated 2 years ago
- [NeurIPS 2022] SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training☆34Updated last year
- KDD 2023 accepted paper, FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy☆25Updated last week
- [ICML 2023] FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction☆25Updated 8 months ago
- [KDD2021] Federated Adversarial Debiasing for Fair and Transferable Representations: Optimize an adversarial domain-adaptation objective …☆26Updated last year
- Code release for Tackling Data Heterogeneity in Federated Learning with Class Prototypes appeared on AAAI2023.☆38Updated last year
- Practical One-Shot Federated Learning for Cross-Silo Setting☆42Updated 3 years ago
- Rethinking Data Heterogeneity in Federated Learning: Introducing a New Notion and Standard Benchmarks☆24Updated 2 years ago
- CVPR 2022: FedCorr: Multi-Stage Federated Learning for Label Noise Correction☆34Updated 8 months ago
- Official repository for Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning [CVPR 2022 Oral, Best Paper Finalist]☆55Updated 2 years ago
- ☆31Updated 2 years ago
- Code for ICLR 2023 Paper Better Generative Replay for Continual Federated Learning☆27Updated last year
- Confidence-aware Personalized Federated Learning via Variational Expectation Maximization [Accepted at CVPR 2023]☆16Updated last year
- FedUL: Federated Learning from Only Unlabeled Data with Class-Conditional-Sharing Clients☆33Updated last year
- ☆22Updated 3 years ago
- AAAI 2024 accepted paper, FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heter…☆38Updated last week
- [NeurIPS'22 Spotlight] Federated Learning from Pre-Trained Models: A Contrastive Learning Approach☆42Updated last year
- Code for CVPR2023 DaFKD : Domain-aware Federated Knowledge Distillation☆26Updated last year
- Benchmarking Semi-supervised Federated Learning☆51Updated 2 years ago
- [ICLR2023] Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning (https://arxiv.org/abs/2210.0022…☆40Updated last year
- Official code for "Personalized Federated Learning through Local Memorization" (ICML'22)☆42Updated last year
- ☆43Updated 2 years ago
- [NeurIPS'23] FedL2P: Federated Learning to Personalize☆19Updated 4 months ago
- Source code for the ICML 2022 paper: "Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering"☆53Updated last year
- ☆21Updated 2 years ago
- ☆18Updated 2 years ago
- CVPR 2024 - Fair Federated Learning under Domain Skew with Local Consistency and Domain Diversity☆15Updated 5 months ago
- [ICML2022] ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training☆20Updated 2 years ago
- Federated Learning with New Knowledge -- explore to incorporate various new knowledge into existing FL systems and evolve these systems t…☆80Updated 9 months ago