Zhicheng Yao

Distribution-Aware Energy Minimization: Physical-Inspired Efficient Active Learning and Quantum Potentials

Active learning aims to maximize model performance with minimal annotation costs by selecting the most informative samples from large unlabeled pools, which often face a budget dilemma: uncertainty-based methods induce redundancy under low budgets, while representativeness-based methods struggle to