2 papers
cs.AI2026
Robust Regularized Policy Iteration under Transition Uncertainty
Hongqiang Lin, Zhenghui Fu, Weihao Tang +4
Offline reinforcement learning (RL) enables data-efficient and safe policy learning without online exploration, but its performance often degrades under distribution shift. The lea…
cs.LG2026
Dual-Phase Federated Deep Unlearning via Weight-Aware Rollback and Reconstruction
Changjun Zhou, Jintao Zheng, Leyou Yang +1
Federated Unlearning (FUL) focuses on client data and computing power to offer a privacy-preserving solution. However, high computational demands, complex incentive mechanisms, and…