December 18, 2023
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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”
