3 accepted papers
Offline-to-online reinforcement learning (O2O RL) faces a central challenge between retaining offline conservatism and adapting to online feedback under distribution shift. This challenge arises because data behavior evolves during fine-tuning, rendering data origin a misleading basis for constraint…
Micro-expressions (MEs) are brief, low-intensity, often localized facial expressions. They could reveal genuine emotions individuals may attempt to conceal, valuable in contexts like criminal interrogation and psychological counseling. However, ME recognition (MER) faces challenges, such as small sa…
Structured pruning is a popular technique for reducing the computational cost and memory footprint of neural networks by removing channels. It often leads to a decrease in network accuracy, which can be restored through fine-tuning. However, as the pruning ratio increases, it becomes progressively m…