Our group had a fun week at NeurIPS’23 presenting three papers:

 "A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks”

"SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models”
Best Paper at FL@FM-NeurIPS’23

 "FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System”