3 papers
cs.LG2025
Multi-granularity Knowledge Transfer for Continual Reinforcement Learning
Chaofan Pan, Lingfei Ren, Yihui Feng +4
Continual reinforcement learning (CRL) empowers RL agents with the ability to learn a sequence of tasks, accumulating knowledge learned in the past and using the knowledge for prob…
cs.LG2025
Ten Challenging Problems in Federated Foundation Models
Tao Fan, Hanlin Gu, Xuemei Cao +30
Federated Foundation Models (FedFMs) represent a distributed learning paradigm that fuses general competences of foundation models as well as privacy-preserving capabilities of fed…
cs.LG2025
A New Perspective on Privacy Protection in Federated Learning with Granular-Ball Computing
Guannan Lai, Yihui Feng, Xin Yang +5
Federated Learning (FL) facilitates collaborative model training while prioritizing privacy by avoiding direct data sharing. However, most existing articles attempt to address chal…