Pinned Repositories
Cross-modal-Retrieval
Cross-Modal-Real-valuded-Retrieval
easyFL
An experimental platform to quickly realize and compare with popular centralized federated learning algorithms. A realization of federated learning algorithm on fairness (FedFV, Federated Learning with Fair Averaging, https://fanxlxmu.github.io/publication/ijcai2021/) was accepted by IJCAI-21 (https://www.ijcai.org/proceedings/2021/223).
FCH-PPE
Probabilistic Prototype Encoding for Federated Cross-modal Hashing Retrieval
FCPO
code for ‘Towards Long-term Fairness in Recommendation’
FedProto
[AAAI'22] FedProto: Federated Prototype Learning across Heterogeneous Clients
FedReID
Implementation of Federated Learning to Person Re-identification (Code for ACMMM 2020 paper)
FedRepo
FedUCH
FedUCH
FL-bench
Benchmark of federated learning. Dedicated to the community. 🤗
PT-FUCH_P
PT-FUCH
Tam-JQK's Repositories
Tam-JQK/PT-FUCH_P
PT-FUCH
Tam-JQK/easyFL
An experimental platform to quickly realize and compare with popular centralized federated learning algorithms. A realization of federated learning algorithm on fairness (FedFV, Federated Learning with Fair Averaging, https://fanxlxmu.github.io/publication/ijcai2021/) was accepted by IJCAI-21 (https://www.ijcai.org/proceedings/2021/223).
Tam-JQK/Cross-modal-Retrieval
Cross-Modal-Real-valuded-Retrieval
Tam-JQK/FCH-PPE
Probabilistic Prototype Encoding for Federated Cross-modal Hashing Retrieval
Tam-JQK/FCPO
code for ‘Towards Long-term Fairness in Recommendation’
Tam-JQK/FedProto
[AAAI'22] FedProto: Federated Prototype Learning across Heterogeneous Clients
Tam-JQK/FedReID
Implementation of Federated Learning to Person Re-identification (Code for ACMMM 2020 paper)
Tam-JQK/FedRepo
Tam-JQK/FedUCH
FedUCH
Tam-JQK/FL-bench
Benchmark of federated learning. Dedicated to the community. 🤗
Tam-JQK/ML_Notes
机器学习算法的公式推导以及numpy实现
Tam-JQK/MOON
Model-Contrastive Federated Learning (CVPR 2021)
Tam-JQK/RethinkFL
CVPR2023 - Rethinking Federated Learning with Domain Shift: A Prototype View
Tam-JQK/variational-fairness
Enhancing Long Term Fairness in Recommendations with Variational Autoencoders