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cs.LG2026
Continual Learning in Transition
Zhiyan Hou, Dan Zhang, Tao Feng +11
Classical continual learning (CL) has primarily focused on enabling models to update and retain knowledge through parameter-centric mechanisms, e.g., training strategies, architect…
cs.LG2026
Labeled TrustSet Guided: Batch Active Learning with Reinforcement Learning
Guofeng Cui, Yang Liu, Pichao Wang +4
Batch active learning (BAL) is a crucial technique for reducing labeling costs and improving data efficiency in training large-scale deep learning models. Traditional BAL methods o…