FL-TAC: Enhanced Fine-Tuning in Federated Learning via Low-Rank, Task-Specific Adapter Clustering.
Siqi PingYuzhu MaoYang LiuXiao-Ping ZhangWenbo DingPublished in: CoRR (2024)
Keyphrases
- fine tuning
- low rank
- learning process
- unsupervised learning
- learning problems
- learning tasks
- reinforcement learning
- matrix factorization
- clustering method
- clustering algorithm
- matrix completion
- high order
- supervised learning
- learning algorithm
- high dimensional data
- linear combination
- data analysis
- pattern recognition
- group sparsity